IBM Capstone Project - Identifying the best US city to host the next 'Laver Cup - 2020'

Introduction:

The "Laver Cup" is a Tennis Tournament organized each year, in the month of September, for a 3 days showdown of the world's top Tennis talents in the world, competing against one another. The "Laver Cup" pits six top European players against six of their counterparts from the rest of the World. One of the prime reasons to introduce the "Laver Cup" is to diversify, advocate and market the sport of Tennis to the entire world and also to lesser famous Tennis destinations of the world, where the sport is not a top event of the city. In a similar vein, the location of the "Laver Cup" rotates between Europe and rest of the world cities, each year. The "Laver Cup" was brought to life in 2017 and has been a mega-success since its inception. The Cup was inaugurated in Prague, Czech Republic in 2017, it then travelled to the US for the 1st time in 2018, in Chicago and back to Europe (Geneva, Switzerland), in 2019. In summary:

  1. 2017 - Prague, Czech Republic, Europe
  2. 2018 - Chicago, Illinois, US
  3. 2019 - Geneva, Switzerland, Europe

Business Problem:

The Laver Cup committee has been tasked to host the next Laver Cup, scheduled in September, 2020 in one of the major US cities. A number of major US cities entered the draw, out of which a total of 6 major US cities are shortliste, from the random draw. From the 6 major US cities, the Laver Cup committee must choose a city, from the final 6 cities, to host the Cup. The committee must ensure that the city will be ready from an infrastructure stand-point, to ensure the facilities in and around the main stadium are developed to support a flush of world audience. The committee must also ensure the neighborhood around the stadium is conducive to support a strong sports culture and captivate the Tennis audience for an ultimate fan experience.

Methodology:

To help the choose the next best US city to host "Laver Cup - 2020", the Tennis stadiums of the 4 major Grand Slams will be explored along with the 3 city centers which have hosted the Laver Cups, in the past. A master data set of all the 7 major stadiums (4 Grand Slam stadiums + 3 Laver Cup stadiums) will be created to cluster the stadiums and explore the similarity between the 7 stadiums.

Next, the 6 candidate city stadiums, in the US, will be explored in a dataframe (DF). The venues around these stadiums will be categorized and the frequency of the venue categories will be explored around each of the 6 city stadiums and compared against the 7 major world stadiums (found earlier).

To compare the 6 candidate US cities with the 7 major stadiums, a concatenated "Master Tennis Dataset" will be created which will include the frequency of venue categories against each of 13 major city stadiums (6 candidates + 7 historical stadiums).

ML model(s): A "KMeans" clustering algorithm will be utilized to segregate the 6 candidate city stadiums into different clusters. A pattern based algorithm was chosen here, since the dataset contains historical, static data on which the KMeans is known to perform with acceptable accuracy. In order to decide the number of clusters to solve each of the problems/ datasets, 2 optimization techniques were utilized:

  1. The Elbow Method - This computes the "WSS" or 'within-sum-of-squares' error through finding the euclidian distance of each of the data points within a cluster to the center of other clusters. The point (number of clusters) where the "WSS" loss tends to flatten out (or create an elbow point), is the optimal number of clusters to use for the given dataset.
  2. The Silhoutte Method - This method measures the similarity of an object within a cluster with other objects within the same cluster (cohesiveness) and compares it with the dissimilarity of the object with other clusters (separation). The Silhoutte score ranges from -1 to +1. A high value implies an appropriate clustering configuration, while lower values imply that number of clusters are too many or too few (i.e. the object in the cluster could be better classified compared to other clusters in the dataset). In the graph, the highest point (number of clusters with highest value), is considered as the optimal number of clusters.

Analysis:

After running the "KMeans" algorithm on the "Master Tennis Dataset", the candidate states / candidate cities (out of the 6), which are most similar to US Open and Chicago-Laver Cup event (i.e. if fall under the same cluster), were considered the best cities to host the next Laver Cup. Again, measurement metric utilized is 'Neighborhood Similarity'. The US Open was taken as the baseline as it is a considered a good attraction point for many sport enthusiasts and Tennis fans alike, being one of the 4 major Tennis destinations of world.

City Stadium exploration:

Of the candidate cities which fall under the same cluster as "US Open" and "Chicago-Laver-Cup", each of thsoe cities was explored on a map to visualize the sports, tourism, entertainment and food infrastructure around the stadium. This is significant to understand if the city os ready to host a world event within a 10 months time-period. Candidate cities, for which, the neighborhood was not well developed to support a huge inlfux of sports tourism, were discarded (e.g. Miami, FL was found to be under-developed in this respect and was discarded).

Final Analysis:

Of the candidate cities which were left, a final clustering algorithm was run, to find the city neighborhood which is closest to the US Open.

Data Source:

The Foursquare API was utilized to extract, load raw JSON, filter, structure into a DF and analyze datasets around the major Tennis stadiums of the world. For historical datasets, 7 major Tennis stadiums (4 Grand Slams stadiums + 3 Past Laver Cup stadiums) was explored using the 'search' criteria around the stadium locations using the Foursquare API (Account). The addresses used, for venues exploration, were as follows:

  1. Australian Open --> 'Rod Laver Arena, Victoria, Australia'
  2. US Open --> 'Flushing Meadows, Queens, NY'
  3. Wimbledon --> 'Wimbledon, London, UK'
  4. French Open --> '2 Avenue Gordon Bennett, Paris, France'
  5. Laver Cup 2017 --> 'O2 Arena, Prague, Czech Republic'
  6. Laver Cup 2018 --> 'United Center, Chicago, Illinois'
  7. Laver Cup 2019 --> 'Palexpo, Geneva, Switzerland'

Similarly, the 'search' criteria was used for the 6 candidate cites, to explore the venues around each of the city stadiums. The addresses used were as follows:

  1. Miami --> 'Crandon Park, Miami, FL'
  2. Cincinatti --> 'Lindner Family Tennis Center, OH'
  3. Palm Springs --> 'Indian Wells, Coachella Valley, CA'
  4. Boston --> 'TD Garden, Boston, MA'
  5. Arizona --> 'Arizona Veterans Memorial, AZ'
  6. Dallas --> 'American Airlines Center, Victory Park, Dallas, TX'

Execution & Analysis:

Finding the 'latitude' and 'logitudes' of each of the 4 major Tennis stadiums and past 3 Laver Cup venues (7 Tennis stadiums):

Finding the latitude and longitude of all venues: 
[Latitude, Longitude]
 
French Open Location: 2 Avenue Gordon Bennett, Paris, France
48.8466913 2.2510958
 
Australian Open Location: Rod Laver Arena, Victoria, Australia
-37.821568799999994 144.978587525521
 
US Open, Location: USTA Billie Jean King National Tennis Center, Queens, NY
40.74957645 -73.84654175507845
 
Wimbledon, Location: Wimbledon, London, UK
51.4214787 -0.2064027
 
Laver Cup 1, Location: O2 Arena, Prague, Czech Republic
50.104754650000004 14.493621810111105
 
Laver Cup 2, Location: United Center, Chicago, Illinois
41.88068305 -87.67418510441388
 
Laver Cup 3, Location: Palexpo, Geneva, Switzerland
46.2332822 6.1184341

Setting up the client ID, Client Secret and Version of the API call:

Your credentails:
CLIENT_ID: 4U1D1Y4NBCWGRWG0AQ4OWDDCTYA13HNM3FRZBJIA3ES5ZN5Q
CLIENT_SECRET:FPLOCTRVGFFZ5Q4X5GFNPAOPZ4SCWPVHEG2QNDSKFZJ22QYE

Filtering the json file to store on the relevant data, converting it to a structured Pandas DF and exploring the columns of the DF:

categories hasPerk id location.address location.cc location.city location.country location.crossStreet location.distance location.formattedAddress location.labeledLatLngs location.lat location.lng location.postalCode location.state name referralId venuePage.id
0 [{'id': '4bf58dd8d48988d127941735', 'name': 'C... False 4d6e383d30d5b1f7bcaec342 Palexpo CH Le Grand-Saconnex Suisse Route François-Peyrot 30 194 [Palexpo (Route François-Peyrot 30), 1218 Gran... [{'label': 'display', 'lat': 46.23470047580338... 46.234700 6.119900 1218 Genève Centre de presse de Palexpo v-1582419989 NaN
1 [{'id': '4bf58dd8d48988d1ff931735', 'name': 'C... False 4adcdab4f964a520855021e3 Route François-Peyrot 30 CH Le Grand-Saconnex Suisse NaN 142 [Route François-Peyrot 30, 1218 Le Grand-Sacon... [{'label': 'display', 'lat': 46.2343739420567,... 46.234374 6.119406 1218 Genève Palexpo v-1582419989 NaN
2 [{'id': '4bf58dd8d48988d1e2931735', 'name': 'A... False 5888d0a5409f56237f153232 NaN CH NaN Schweiz NaN 76 [Schweiz] [{'label': 'display', 'lat': 46.233673, 'lng':... 46.233673 6.119245 NaN NaN Art Genève v-1582419989 NaN
3 [{'id': '4bf58dd8d48988d1fa931735', 'name': 'H... False 5a8467821755625497c90bf4 Route Francois Peyrot 28 CH Le Grand-Saconnex Suisse NaN 184 [Route Francois Peyrot 28, 1218 Le Grand Sacon... [{'label': 'display', 'lat': 46.234896, 'lng':... 46.234896 6.117870 1218 Genève ibis Budget Genève Palexpo Aéroport v-1582419989 NaN
4 [{'id': '4bf58dd8d48988d147941735', 'name': 'D... False 4f794bfce4b087957c5ca19d NaN CH NaN Schweiz NaN 93 [Schweiz] [{'label': 'display', 'lat': 46.234032545323, ... 46.234033 6.117885 NaN NaN Bar Restaurant Le Poivrier v-1582419989 NaN

Cleaning up the structured DF and cleaning column values, to include only the relevant columns:

Event name categories lat lng
0 French Open Jardin des Serres d'Auteuil Botanical Garden 48.846509 2.252549
1 French Open Loge Orange Stadium 48.846544 2.250335
2 French Open Jardins de Roland Garros Garden 48.847124 2.250180
3 French Open Restaurant Le Roland Garros French Restaurant 48.847226 2.250683
4 French Open Court n°1 Tennis Court 48.846608 2.250470
Event name categories lat lng
0 Wimbledon Wimbledon Railway Station (WIM) Train Station 51.421862 -0.205460
1 Wimbledon Digby's Coffee Shop 51.421402 -0.206698
2 Wimbledon Wimbledon London Underground Station Metro Station 51.421912 -0.205681
3 Wimbledon Costa Coffee Coffee Shop 51.421609 -0.206353
4 Wimbledon Platform 5 Platform 51.421321 -0.206154

Creating a master dataset of all 7 tennis stadiums by concatenating it into one large dataset:

Event name categories lat lng
95 Rod_Laver_Swizz Banque Cantonale de Genève - Grand-Saconnex Bank 46.233476 6.123379
96 Rod_Laver_Swizz Consulat General de Turquie Government Building 46.232052 6.115695
97 Rod_Laver_Swizz Canicrok Pet Store 46.230860 6.118221
98 Rod_Laver_Swizz Bar Chez Tito Restaurant 46.231095 6.118680
99 Rod_Laver_Swizz la tour None 46.230337 6.121895

Applying One-Hot-Encoding to the Dataframe, to categorize each of the venues into a column format:

(700, 214)
Event_Venue American Restaurant Art Gallery Arts & Crafts Store Arts & Entertainment Asian Restaurant Athletics & Sports Auditorium Australian Restaurant Automotive Shop BBQ Joint Baby Store Bagel Shop Bakery Bank Bar Basketball Court Basketball Stadium Beach Beer Bar Beer Garden Bike Rental / Bike Share Bistro Boat or Ferry Bookstore Botanical Garden Boutique Brewery Bridal Shop Bridge Buffet Building Burger Joint Bus Line Bus Station Bus Stop Business Center Café Camera Store Candy Store Casino Chinese Restaurant Church Circus Clothing Store Cocktail Bar Coffee Shop College Baseball Diamond College Classroom College Stadium Comedy Club Concert Hall Conference Room Convention Center Corporate Cafeteria Cosmetics Shop Coworking Space Creperie Cuban Restaurant Deli / Bodega Diner Doctor's Office Donut Shop Eastern European Restaurant Event Space Exhibit Factory Fair Farm Fast Food Restaurant Food & Drink Shop Food Court Food Service Food Truck Fountain French Restaurant Fried Chicken Joint Furniture / Home Store Garden Gas Station General Entertainment Gift Shop Gourmet Shop Government Building Grocery Store Gym Gym / Fitness Center Hardware Store Health & Beauty Service High School Historic Site History Museum Hockey Arena Hockey Field Hot Dog Joint Hotel Hotel Bar Hotel Pool Ice Cream Shop Indian Restaurant Indoor Play Area Italian Restaurant Jewelry Store Juice Bar Karaoke Bar Kitchen Supply Store Korean Restaurant Laundry Service Light Rail Station Lingerie Store Liquor Store Lounge Massage Studio Mediterranean Restaurant Meeting Room Men's Store Metro Station Mexican Restaurant Middle School Mini Golf Miscellaneous Shop Mobile Phone Shop Monument / Landmark Movie Theater Museum Music Venue Nightclub Office Optical Shop Other Great Outdoors Other Repair Shop Outdoor Event Space Outdoor Sculpture Outdoors & Recreation Paper / Office Supplies Store Park Parking Performing Arts Venue Perfume Shop Pet Store Pharmacy Photography Lab Physical Therapist Pizza Place Platform Plaza Police Station Pool Pool Hall Post Office Pub Public Art Public Bathroom Real Estate Office Recreation Center Recycling Facility Rental Car Location Residential Building (Apartment / Condo) Restaurant Rock Club Roof Deck Rugby Stadium Salad Place Salon / Barbershop Sandwich Place Scenic Lookout Sculpture Garden Seafood Restaurant Shoe Repair Shoe Store Shopping Plaza Skating Rink Smoke Shop Snack Place Soccer Stadium Souvenir Shop Spa Sporting Event Sporting Goods Shop Sports Bar Sports Club Stadium Stationery Store Steakhouse Strip Club Supermarket Sushi Restaurant Swiss Restaurant TV Station Taco Place Tailor Shop Tattoo Parlor Taxi Stand Tea Room Tech Startup Temple Tennis Court Tennis Stadium Toy / Game Store Train Station Tram Station Transportation Service Travel Lounge University Vacation Rental Vegetarian / Vegan Restaurant Video Store Warehouse Warehouse Store Whisky Bar Wine Bar Wine Shop Women's Store Yoga Studio
0 French Open 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 French Open 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
2 French Open 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
3 French Open 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
4 French Open 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Aggregating the DF by 'Event_Venue' and finding the mean for each of the categories by 'Event_Venue'.

(7, 214)

Creating a new DF and applying the "get_common_categories" to obtain 10 most common venue categories for each of the 'Event_Venue':

Event_Venue 1st most common venue category 2nd most common venue category 3rd most common venue category 4th most common venue category 5th most common venue category 6th most common venue category 7th most common venue category 8th most common venue category 9th most common venue category 10th most common venue category
0 Aus Open Event Space Tennis Stadium Warehouse Tennis Court General Entertainment Café Concert Hall Food Service Beer Garden Office
1 French Open Tennis Court Stadium Arts & Entertainment French Restaurant College Classroom Event Space Office Sporting Goods Shop Bus Line Supermarket
2 Rod_Laver_Chicago Bar Stadium General Entertainment Outdoor Sculpture Basketball Stadium Sports Bar Hockey Arena Parking Bus Line Sporting Goods Shop
3 Rod_Laver_Czech Lounge Clothing Store Sporting Goods Shop Skating Rink Shoe Store Women's Store Lingerie Store Baby Store Restaurant Cosmetics Shop
4 Rod_Laver_Swizz Convention Center Hotel Event Space Exhibit Café Restaurant Parking Bank Mediterranean Restaurant Fair
5 US Open Tennis Stadium General Entertainment Clothing Store Tennis Court Lounge Sporting Goods Shop Sandwich Place Bar Hot Dog Joint Seafood Restaurant
6 Wimbledon Platform Coffee Shop Bank Fast Food Restaurant Salon / Barbershop Bus Stop Grocery Store Mobile Phone Shop Bar Shoe Repair

Getting the top 25 venue categories for US Open as a comparison basis for other venue categories in other candidate cities:

Event_Venue 1st most common venue category 2nd most common venue category 3rd most common venue category 4th most common venue category 5th most common venue category 6th most common venue category 7th most common venue category 8th most common venue category 9th most common venue category 10th most common venue category 11th most common venue category 12th most common venue category 13th most common venue category 14th most common venue category 15th most common venue category 16th most common venue category 17th most common venue category 18th most common venue category 19th most common venue category 20th most common venue category 21st most common venue category 22nd most common venue category 23rd most common venue category 24th most common venue category 25th most common venue category
5 US Open Tennis Stadium General Entertainment Clothing Store Tennis Court Lounge Sporting Goods Shop Sandwich Place Bar Hot Dog Joint Seafood Restaurant Restaurant Cocktail Bar Event Space Ice Cream Shop Wine Bar Food Court Office Public Art Sculpture Garden Indian Restaurant Chinese Restaurant Salad Place Italian Restaurant Korean Restaurant Fried Chicken Joint

Visualizing the map of US Open and exploring the venue categories around the US Open stadium at 'Flushing Meadows':

Running the 'Elbow-Method' and 'Silhoutte' to determine the optimal number of clusters to initiate for classification of 'Event Venue'.

[2 3 4 5 6] [0.15931380382831367, 0.11579927781493025, 0.07895378241672514, 0.07502260508320509, 0.05345227175645256]

Executing the 'KMeans' algorithm to label the 7 Tennis Venues into 2 clusters (2 clusters were chosen due to highest score at 2 clusters using the 'Silhouette' method):

array([1, 0, 0, 0, 0, 1, 0])

Inserting the 'Cluster Labels' column into the classification DF containing the 10 most common venues for each of the Tennis Stadiums:

Event_Venue Latitude Longitude Cluster Labels 1st most common venue category 2nd most common venue category 3rd most common venue category 4th most common venue category 5th most common venue category 6th most common venue category 7th most common venue category 8th most common venue category 9th most common venue category 10th most common venue category 11th most common venue category 12th most common venue category 13th most common venue category 14th most common venue category 15th most common venue category 16th most common venue category 17th most common venue category 18th most common venue category 19th most common venue category 20th most common venue category 21st most common venue category 22nd most common venue category 23rd most common venue category 24th most common venue category 25th most common venue category
0 French Open 48.846691 2.251096 0 Tennis Court Stadium Arts & Entertainment French Restaurant College Classroom Event Space Office Sporting Goods Shop Bus Line Supermarket Sandwich Place Building Bus Stop Restaurant Tennis Stadium Lounge Gas Station Garden Other Great Outdoors Shopping Plaza Middle School Soccer Stadium Café Real Estate Office Rugby Stadium
1 US Open 40.749576 -73.846542 1 Tennis Stadium General Entertainment Clothing Store Tennis Court Lounge Sporting Goods Shop Sandwich Place Bar Hot Dog Joint Seafood Restaurant Restaurant Cocktail Bar Event Space Ice Cream Shop Wine Bar Food Court Office Public Art Sculpture Garden Indian Restaurant Chinese Restaurant Salad Place Italian Restaurant Korean Restaurant Fried Chicken Joint
2 Aus Open -37.821569 144.978588 1 Event Space Tennis Stadium Warehouse Tennis Court General Entertainment Café Concert Hall Food Service Beer Garden Office Food & Drink Shop Tea Room Bar Bridge Coworking Space Australian Restaurant College Baseball Diamond Park Souvenir Shop Pizza Place Monument / Landmark Plaza Camera Store Music Venue Scenic Lookout
3 Wimbledon 51.421479 -0.206403 0 Platform Coffee Shop Bank Fast Food Restaurant Salon / Barbershop Bus Stop Grocery Store Mobile Phone Shop Bar Shoe Repair Cosmetics Shop Office Shoe Store Sushi Restaurant Snack Place Spa Stationery Store Sandwich Place Food Court Building Metro Station Business Center Furniture / Home Store Clothing Store Cocktail Bar
4 Rod_Laver_Czech 50.104755 14.493622 0 Lounge Clothing Store Sporting Goods Shop Skating Rink Shoe Store Women's Store Lingerie Store Baby Store Restaurant Cosmetics Shop Office Meeting Room Public Bathroom General Entertainment Jewelry Store Kitchen Supply Store Men's Store Café Candy Store Casino Hockey Arena Cocktail Bar Hockey Field Indoor Play Area Residential Building (Apartment / Condo)
5 Rod_Laver_Chicago 41.880683 -87.674185 0 Bar Stadium General Entertainment Outdoor Sculpture Basketball Stadium Sports Bar Hockey Arena Parking Bus Line Sporting Goods Shop Concert Hall Music Venue Restaurant Bus Stop Fried Chicken Joint Circus Vegetarian / Vegan Restaurant Hot Dog Joint Brewery Office Food Court Indian Restaurant Rock Club Movie Theater Food Truck
6 Rod_Laver_Swizz 46.233282 6.118434 0 Convention Center Hotel Event Space Exhibit Café Restaurant Parking Bank Mediterranean Restaurant Fair Historic Site Gym Lounge Wine Shop Pet Store Art Gallery Conference Room Rental Car Location Meeting Room Bus Line Bus Station Sandwich Place Fast Food Restaurant Diner Residential Building (Apartment / Condo)

Constructing the URL and storing venues and categories of venues around the 6 candidate US cities (listed below) in a raw JSON format:

Miami Location: 7300 Crandon Blvd, Miami, FL
25.70876075 -80.15998756670277
 
Cincinatti Location: Lindner Family Tennis Center, OH
39.34637095 -84.27727893436321
 
Palm Springs Open, Location: Indian Wells, Coachella Valley, CA
33.743764999999996 -116.22331524966393
 
Boston, Location: TD Garden, Boston, MA
42.36628265 -71.06221907010776
 
Arizona, Location: Arizona Veterans Memorial, AZ
35.0940824 -114.6341331
 
Dallas, Location: American Airlines Center, Victory Park, Dallas, TX
32.7905076 -96.81027213460834
 

Transforming the Raw JSON to a structured dataframe containing data columns:

categories hasPerk id location.address location.cc location.city location.country location.crossStreet location.distance location.formattedAddress location.labeledLatLngs location.lat location.lng location.postalCode location.state name referralId venuePage.id
0 [{'id': '5109983191d435c0d71c2bb1', 'name': 'T... False 4dd6f027d22d38ef42dc3f07 6300 Kings Island Dr US Mason United States NaN 382 [6300 Kings Island Dr, Mason, OH 45040, United... [{'label': 'display', 'lat': 39.3430659430824,... 39.343066 -84.276067 45040 OH Kings Island T-Rex v-1582420012 NaN
1 [{'id': '4e39a891bd410d7aed40cbc2', 'name': 'T... False 57b4a7d7498e434792b6600a 5460 Courseview Drive US Mason United States NaN 439 [5460 Courseview Drive, Mason, OH 45220, Unite... [{'label': 'display', 'lat': 39.350094, 'lng':... 39.350094 -84.275597 45220 OH Western Southern Open v-1582420012 NaN
2 [{'id': '4bf58dd8d48988d1e6941735', 'name': 'G... False 4bb62b6e6edc76b0c380301c 6042 Fairway Dr US Mason United States NaN 431 [6042 Fairway Dr, Mason, OH 45040, United States] [{'label': 'display', 'lat': 39.35017034332829... 39.350170 -84.278301 45040 OH Kings Island Golf Course v-1582420012 NaN
3 [{'id': '4f2a210c4b9023bd5841ed28', 'name': 'H... False 500c7122e4b0ba42c29d1b9a NaN US Mason United States NaN 320 [Mason, OH 45040, United States] [{'label': 'display', 'lat': 39.34721740017701... 39.347217 -84.273723 45040 OH Pine Run v-1582420012 NaN
4 [{'id': '4bf58dd8d48988d182941735', 'name': 'T... False 59b89e1db8fd9d24795639c1 NaN US Maineville United States NaN 240 [Maineville, OH 45039, United States] [{'label': 'display', 'lat': 39.344765, 'lng':... 39.344765 -84.275410 45039 OH Maineville, Oh v-1582420012 NaN

Filtering out the DF to include relevant columns:

name categories location.city location.state location.lat location.lng
0 Kings Island T-Rex [{'id': '5109983191d435c0d71c2bb1', 'name': 'T... Mason OH 39.343066 -84.276067
1 Western Southern Open [{'id': '4e39a891bd410d7aed40cbc2', 'name': 'T... Mason OH 39.350094 -84.275597
2 Kings Island Golf Course [{'id': '4bf58dd8d48988d1e6941735', 'name': 'G... Mason OH 39.350170 -84.278301
3 Pine Run [{'id': '4f2a210c4b9023bd5841ed28', 'name': 'H... Mason OH 39.347217 -84.273723
4 Maineville, Oh [{'id': '4bf58dd8d48988d182941735', 'name': 'T... Maineville OH 39.344765 -84.275410

Cleaning up the column names:

name categories city state lat lng
0 Kings Island T-Rex Theme Park Ride / Attraction Mason OH 39.343066 -84.276067
1 Western Southern Open Tennis Stadium Mason OH 39.350094 -84.275597
2 Kings Island Golf Course Golf Course Mason OH 39.350170 -84.278301
3 Pine Run Housing Development Mason OH 39.347217 -84.273723
4 Maineville, Oh Theme Park Maineville OH 39.344765 -84.275410

Cleaining up the DF to include only unique state values in the 'state' column of the DF (for e.g. convert 'Arizona' to 'AZ' and 'Massachusetts' to 'MA'):

name categories city state lat lng
0 Paulaner Bar Bar Boston MA 42.366235 -71.062060
1 TD Garden Hockey Arena Boston MA 42.366329 -71.062153
2 MBTA North Station Train Station Boston MA 42.366242 -71.062338
3 Track 9 Platform Boston MA 42.366979 -71.063192
4 Track 8 Platform Boston MA 42.367022 -71.063099

Further cleaning up the DF, excluding irrelevant 'state' values, aggregating the DF by 'state' and finding the mean number of categories for each of the 6 states / candidate cities

(6, 182)
state ATM Accessories Store Advertising Agency American Restaurant Arcade Art Gallery Arts & Crafts Store Athletics & Sports Auditorium Automotive Shop BBQ Joint Bakery Bank Bar Baseball Field Basketball Court Basketball Stadium Beach Beer Garden Big Box Store Bike Shop Boat or Ferry Boutique Buffet Building Burger Joint Bus Line Business Center Business Service Café Capitol Building Church Clothing Store Cocktail Bar Coffee Shop Comfort Food Restaurant Concert Hall Conference Room Construction & Landscaping Convenience Store Cosmetics Shop Coworking Space Cuban Restaurant Deli / Bodega Dentist's Office Department Store Dessert Shop Diner Discount Store Dive Bar Doctor's Office Dog Run Donut Shop EV Charging Station Electronics Store Event Space Fabric Shop Factory Fast Food Restaurant Field Fire Station Fish & Chips Shop Food Food & Drink Shop Food Court Food Service Food Truck Fried Chicken Joint Gas Station Gastropub General Entertainment General Travel German Restaurant Gift Shop Golf Course Government Building Grocery Store Gym Gym / Fitness Center Harbor / Marina Hardware Store High School Historic Site Hockey Arena Hockey Field Hospital Hot Dog Joint Hotel Hotel Bar Housing Development Ice Cream Shop Italian Restaurant Juice Bar Kids Store Latin American Restaurant Laundry Service Light Rail Station Liquor Store Lounge Market Massage Studio Mediterranean Restaurant Mexican Restaurant Middle School Miscellaneous Shop Mobile Phone Shop Movie Theater Moving Target Museum Music Venue Nail Salon Newsstand Nightclub Nightlife Spot Non-Profit Office Other Great Outdoors Other Nightlife Park Parking Performing Arts Venue Peruvian Restaurant Pet Service Pharmacy Photography Lab Pizza Place Planetarium Platform Playground Plaza Police Station Pool Post Office Preschool Professional & Other Places Radio Station Residential Building (Apartment / Condo) Restaurant River Rock Club Roof Deck Salon / Barbershop Sandwich Place School Shopping Mall Skate Park Skating Rink Snack Place Soccer Field Souvenir Shop Spa Speakeasy Sporting Goods Shop Sports Bar Stadium Storage Facility Student Center Supplement Shop Surf Spot TV Station Taco Place Tattoo Parlor Tech Startup Temple Tennis Court Tennis Stadium Thai Restaurant Theater Theme Park Theme Park Ride / Attraction Thrift / Vintage Store Toll Booth Tourist Information Center Trail Train Station Tram Station University Video Store Water Park Wine Bar Women's Store
0 AZ 0.000000 0.00 0.00 0.020202 0.00 0.00 0.000000 0.00 0.010101 0.030303 0.000000 0.020202 0.010101 0.030303 0.020202 0.010101 0.00 0.00 0.010101 0.000000 0.00 0.00 0.00 0.000000 0.070707 0.010101 0.00 0.00 0.00 0.000000 0.010101 0.040404 0.00000 0.00 0.010101 0.00 0.000000 0.010101 0.00 0.040404 0.020202 0.000000 0.00 0.000000 0.020202 0.000000 0.000000 0.010101 0.010101 0.020202 0.000000 0.010101 0.000000 0.000000 0.000000 0.000000 0.010101 0.00 0.000000 0.010101 0.00 0.00 0.010101 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.010101 0.00 0.000000 0.00 0.010101 0.010101 0.020202 0.000000 0.010101 0.010101 0.010101 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010101 0.020202 0.00 0.000000 0.00 0.010101 0.00 0.00 0.000000 0.000000 0.010101 0.00 0.030303 0.010101 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.010101 0.00 0.010101 0.000000 0.010101 0.010101 0.010101 0.000000 0.000000 0.010101 0.010101 0.000000 0.00 0.010101 0.010101 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.010101 0.00 0.000000 0.00 0.010101 0.010101 0.00 0.030303 0.010101 0.010101 0.000000 0.010101 0.00 0.000000 0.010101 0.00 0.000000 0.010101 0.000000 0.010101 0.000000 0.010101 0.000000 0.000000 0.00 0.00 0.010101 0.010101 0.00 0.010101 0.00 0.00 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.010101 0.000000 0.000000 0.000000 0.010101 0.00 0.000000 0.000000
1 CA 0.000000 0.00 0.00 0.000000 0.00 0.00 0.016393 0.00 0.000000 0.032787 0.000000 0.000000 0.032787 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.032787 0.00 0.00 0.00 0.000000 0.065574 0.000000 0.00 0.00 0.00 0.032787 0.000000 0.016393 0.04918 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.016393 0.032787 0.00 0.016393 0.000000 0.032787 0.000000 0.000000 0.016393 0.000000 0.032787 0.000000 0.016393 0.016393 0.016393 0.000000 0.000000 0.00 0.016393 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.016393 0.000000 0.00 0.000000 0.00 0.000000 0.016393 0.016393 0.032787 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.016393 0.000000 0.016393 0.00 0.00 0.016393 0.000000 0.00 0.032787 0.00 0.016393 0.00 0.00 0.000000 0.000000 0.000000 0.00 0.032787 0.000000 0.00 0.032787 0.00 0.000000 0.000000 0.000000 0.016393 0.000000 0.000000 0.00 0.000000 0.016393 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.032787 0.00 0.016393 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.032787 0.000000 0.000000 0.016393 0.000000 0.00 0.000000 0.000000 0.00 0.016393 0.000000 0.032787 0.000000 0.000000 0.000000 0.000000 0.016393 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.016393 0.00 0.000000 0.016393
2 FL 0.000000 0.00 0.00 0.020000 0.01 0.01 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.00 0.12 0.000000 0.000000 0.01 0.03 0.01 0.000000 0.000000 0.010000 0.00 0.00 0.00 0.040000 0.000000 0.010000 0.00000 0.00 0.010000 0.00 0.000000 0.000000 0.01 0.010000 0.000000 0.000000 0.02 0.000000 0.000000 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.01 0.01 0.000000 0.01 0.000000 0.000000 0.01 0.000000 0.03 0.00 0.010000 0.010000 0.00 0.000000 0.01 0.000000 0.000000 0.000000 0.010000 0.020000 0.000000 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.01 0.010000 0.00 0.01 0.000000 0.000000 0.000000 0.01 0.000000 0.000000 0.00 0.000000 0.00 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.030000 0.030000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.01 0.01 0.000000 0.00 0.050000 0.02 0.000000 0.000000 0.00 0.010000 0.010000 0.000000 0.010000 0.000000 0.01 0.010000 0.000000 0.00 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.010000 0.000000 0.02 0.00 0.000000 0.000000 0.01 0.000000 0.05 0.02 0.000000 0.00 0.00 0.01 0.000000 0.01 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000
3 MA 0.012048 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.012048 0.000000 0.012048 0.000000 0.000000 0.120482 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.012048 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.000000 0.00000 0.00 0.000000 0.00 0.012048 0.000000 0.00 0.012048 0.012048 0.000000 0.00 0.000000 0.000000 0.000000 0.012048 0.000000 0.000000 0.012048 0.000000 0.000000 0.012048 0.000000 0.000000 0.024096 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.012048 0.012048 0.00 0.012048 0.00 0.00 0.060241 0.000000 0.00 0.012048 0.00 0.000000 0.012048 0.012048 0.000000 0.000000 0.000000 0.000000 0.00 0.072289 0.036145 0.000000 0.012048 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.036145 0.012048 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.024096 0.012048 0.012048 0.000000 0.012048 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.012048 0.000000 0.000000 0.000000 0.00 0.024096 0.000000 0.108434 0.012048 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.012048 0.00 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.024096 0.000000 0.00 0.000000 0.000000 0.024096 0.000000 0.024096 0.000000 0.012048 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.012048 0.012048 0.012048 0.000000 0.00 0.012048 0.000000
4 OH 0.000000 0.01 0.00 0.020000 0.01 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.010000 0.000000 0.00 0.01 0.00 0.020000 0.000000 0.000000 0.01000 0.02 0.010000 0.01 0.000000 0.010000 0.00 0.010000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.020000 0.000000 0.01 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.030000 0.020000 0.01 0.010000 0.03 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.02 0.010000 0.000000 0.01 0.000000 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.000000 0.010000 0.01 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.040000 0.000000 0.000000 0.010000 0.030000 0.000000 0.000000 0.000000 0.000000 0.03 0.010000 0.000000 0.000000 0.010000 0.00 0.01 0.01 0.00 0.00 0.000000 0.00 0.020000 0.00 0.000000 0.010000 0.00 0.010000 0.010000 0.000000 0.000000 0.000000 0.00 0.010000 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.11 0.04 0.000000 0.01 0.07 0.05 0.000000 0.00 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.06 0.000000 0.000000
5 TX 0.000000 0.00 0.01 0.010000 0.00 0.03 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.090000 0.000000 0.020000 0.01 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.020000 0.010000 0.01 0.00 0.01 0.000000 0.000000 0.000000 0.03000 0.02 0.000000 0.00 0.010000 0.010000 0.00 0.010000 0.000000 0.010000 0.00 0.000000 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.060000 0.000000 0.00 0.010000 0.000000 0.00 0.00 0.010000 0.00 0.000000 0.000000 0.01 0.000000 0.01 0.01 0.010000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.000000 0.000000 0.000000 0.010000 0.01 0.00 0.000000 0.030000 0.01 0.000000 0.00 0.000000 0.01 0.00 0.070000 0.000000 0.000000 0.00 0.000000 0.000000 0.02 0.000000 0.00 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.01 0.000000 0.050000 0.010000 0.000000 0.000000 0.060000 0.000000 0.000000 0.000000 0.010000 0.00 0.010000 0.000000 0.000000 0.000000 0.02 0.00 0.00 0.00 0.00 0.000000 0.01 0.050000 0.01 0.000000 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.000000 0.020000 0.070000 0.010000 0.000000 0.000000 0.000000 0.00 0.01 0.000000 0.000000 0.01 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000

Applying the "get_most_common_categories" function on the above DF to find 10 most common categories for each of the candidate stadium locations

state 1st most common venue category 2nd most common venue category 3rd most common venue category 4th most common venue category 5th most common venue category 6th most common venue category 7th most common venue category 8th most common venue category 9th most common venue category 10th most common venue category
0 AZ Event Space Tennis Stadium Warehouse Tennis Court General Entertainment Café Concert Hall Food Service Beer Garden Office
1 CA Tennis Court Stadium Arts & Entertainment French Restaurant College Classroom Event Space Office Sporting Goods Shop Bus Line Supermarket
2 FL Bar Stadium General Entertainment Outdoor Sculpture Basketball Stadium Sports Bar Hockey Arena Parking Bus Line Sporting Goods Shop
3 MA Lounge Clothing Store Sporting Goods Shop Skating Rink Shoe Store Women's Store Lingerie Store Baby Store Restaurant Cosmetics Shop
4 OH Convention Center Hotel Event Space Exhibit Café Restaurant Parking Bank Mediterranean Restaurant Fair
5 TX Tennis Stadium General Entertainment Clothing Store Tennis Court Lounge Sporting Goods Shop Sandwich Place Bar Hot Dog Joint Seafood Restaurant

Determing the optimal number of clusters to initate to classify the 6 candidate locations using 'Elbow Method' and 'Silhoutte Method':

[2 3 4 5] [0.12693762562607663, 0.14068242724701063, 0.10865375560964145, 0.07953041292334136]

Using the result of the 'Silhoutte Method' (number of clusters with highest score)', 3 clusters were chosen to execute the 'KMeans' algorithm:

array([2, 2, 0, 1, 0, 1])

Creating a 'master_tennis_set', a DF including a concatenation of all 7 Tennis venues along with 6 new candidate cities to host the Laver Cup:

Event_Venue American Restaurant Art Gallery Arts & Crafts Store Arts & Entertainment Asian Restaurant Athletics & Sports Auditorium Australian Restaurant Automotive Shop BBQ Joint Baby Store Bagel Shop Bakery Bank Bar Basketball Court Basketball Stadium Beach Beer Bar Beer Garden Bike Rental / Bike Share Bistro Boat or Ferry Bookstore Botanical Garden Boutique Brewery Bridal Shop Bridge Buffet Building Burger Joint Bus Line Bus Station Bus Stop Business Center Café Camera Store Candy Store Casino Chinese Restaurant Church Circus Clothing Store Cocktail Bar Coffee Shop College Baseball Diamond College Classroom College Stadium Comedy Club Concert Hall Conference Room Convention Center Corporate Cafeteria Cosmetics Shop Coworking Space Creperie Cuban Restaurant Deli / Bodega Diner Doctor's Office Donut Shop Eastern European Restaurant Event Space Exhibit Factory Fair Farm Fast Food Restaurant Food & Drink Shop Food Court Food Service Food Truck Fountain French Restaurant Fried Chicken Joint Furniture / Home Store Garden Gas Station General Entertainment Gift Shop Gourmet Shop Government Building Grocery Store Gym Gym / Fitness Center Hardware Store Health & Beauty Service High School Historic Site History Museum Hockey Arena Hockey Field Hot Dog Joint Hotel Hotel Bar Hotel Pool Ice Cream Shop Indian Restaurant Indoor Play Area Italian Restaurant Jewelry Store Juice Bar Karaoke Bar Kitchen Supply Store Korean Restaurant Laundry Service Light Rail Station Lingerie Store Liquor Store Lounge Massage Studio Mediterranean Restaurant Meeting Room Men's Store Metro Station Mexican Restaurant Middle School Mini Golf Miscellaneous Shop Mobile Phone Shop Monument / Landmark Movie Theater Museum Music Venue Nightclub Office Optical Shop Other Great Outdoors Other Repair Shop Outdoor Event Space Outdoor Sculpture Outdoors & Recreation Paper / Office Supplies Store Park Parking Performing Arts Venue Perfume Shop Pet Store Pharmacy Photography Lab Physical Therapist Pizza Place Platform Plaza Police Station Pool Pool Hall Post Office Pub Public Art Public Bathroom Real Estate Office Recreation Center Recycling Facility Rental Car Location Residential Building (Apartment / Condo) Restaurant Rock Club Roof Deck Rugby Stadium Salad Place Salon / Barbershop Sandwich Place Scenic Lookout Sculpture Garden Seafood Restaurant Shoe Repair Shoe Store Shopping Plaza Skating Rink Smoke Shop Snack Place Soccer Stadium Souvenir Shop Spa Sporting Event Sporting Goods Shop Sports Bar Sports Club Stadium Stationery Store Steakhouse Strip Club Supermarket Sushi Restaurant Swiss Restaurant TV Station Taco Place Tailor Shop Tattoo Parlor Taxi Stand Tea Room Tech Startup Temple Tennis Court Tennis Stadium Toy / Game Store Train Station Tram Station Transportation Service Travel Lounge University Vacation Rental Vegetarian / Vegan Restaurant Video Store Warehouse Warehouse Store Whisky Bar Wine Bar Wine Shop Women's Store Yoga Studio ATM Accessories Store Advertising Agency Arcade Baseball Field Big Box Store Bike Shop Business Service Capitol Building Comfort Food Restaurant Construction & Landscaping Convenience Store Dentist's Office Department Store Dessert Shop Discount Store Dive Bar Dog Run EV Charging Station Electronics Store Fabric Shop Field Fire Station Fish & Chips Shop Food Gastropub General Travel German Restaurant Golf Course Harbor / Marina Hospital Housing Development Kids Store Latin American Restaurant Market Moving Target Nail Salon Newsstand Nightlife Spot Non-Profit Other Nightlife Peruvian Restaurant Pet Service Planetarium Playground Preschool Professional & Other Places Radio Station River School Shopping Mall Skate Park Soccer Field Speakeasy Storage Facility Student Center Supplement Shop Surf Spot Thai Restaurant Theater Theme Park Theme Park Ride / Attraction Thrift / Vintage Store Toll Booth Tourist Information Center Trail Water Park
0 Aus Open 0.000000 0.00 0.000000 0.00 0.01 0.00 0.010000 0.02 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.020000 0.000000 0.00 0.00 0.00 0.020000 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.02 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.00 0.040000 0.01 0.00 0.00 0.00 0.000000 0.00 0.01000 0.00 0.010000 0.01 0.00 0.00 0.00 0.030000 0.010000 0.01 0.00 0.000000 0.020000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.150000 0.00 0.00 0.00 0.00 0.000000 0.02 0.000000 0.020000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.050000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.01 0.00 0.01 0.010000 0.000000 0.00 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.010000 0.000000 0.020000 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.01 0.000000 0.00 0.000000 0.010000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.02 0.00 0.000000 0.05 0.13 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.06 0.00 0.00 0.000000 0.00 0.000000 0.00 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
1 French Open 0.000000 0.01 0.000000 0.05 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.000000 0.020000 0.000000 0.02 0.00 0.02 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00000 0.00 0.000000 0.00 0.04 0.01 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.030000 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.04 0.000000 0.00 0.02 0.02 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.010000 0.000000 0.00 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.030000 0.00 0.020000 0.00 0.00 0.00 0.01 0.00 0.010000 0.010000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.000000 0.02 0.010000 0.01 0.01 0.00 0.000000 0.020000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.000000 0.01 0.00 0.010000 0.00 0.030000 0.000000 0.01 0.070000 0.00 0.00 0.00 0.02 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.17 0.02 0.00 0.000000 0.000000 0.00 0.01 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
2 Rod_Laver_Chicago 0.010000 0.00 0.000000 0.01 0.00 0.00 0.000000 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.090000 0.010000 0.05 0.00 0.01 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.000000 0.000000 0.010000 0.03 0.01 0.02 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.02 0.01000 0.00 0.010000 0.00 0.00 0.00 0.00 0.020000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.00 0.00 0.00 0.01 0.000000 0.00 0.010000 0.000000 0.01 0.00 0.00 0.020000 0.00 0.00 0.00 0.060000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.00 0.040000 0.000000 0.020000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.01 0.000000 0.020000 0.000000 0.010000 0.00 0.000000 0.00 0.00 0.06 0.00 0.00 0.000000 0.040000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.02 0.010000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.000000 0.00 0.00 0.000000 0.00 0.030000 0.040000 0.00 0.080000 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.010000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.02 0.000000 0.00 0.00 0.01 0.010000 0.00 0.000000 0.00 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
3 Rod_Laver_Czech 0.000000 0.01 0.010000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.02 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.010000 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.010000 0.010000 0.000000 0.00 0.00 0.00 0.00 0.010000 0.00 0.01 0.01 0.00 0.000000 0.00 0.08000 0.01 0.000000 0.00 0.00 0.00 0.01 0.000000 0.000000 0.01 0.01 0.020000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.00 0.01 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.020000 0.010000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.010000 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.01 0.000000 0.02 0.00 0.01 0.01 0.00 0.010000 0.00 0.03 0.00 0.140000 0.000000 0.00 0.02 0.01 0.00 0.000000 0.000000 0.01 0.01 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.020000 0.00 0.010000 0.01 0.00 0.00 0.00 0.01 0.000000 0.000000 0.000000 0.01 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 0.010000 0.02 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.03 0.00 0.03 0.00 0.000000 0.00 0.00 0.000000 0.00 0.040000 0.010000 0.00 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.01 0.000000 0.01 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.030000 0.00 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
4 Rod_Laver_Swizz 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.00 0.010000 0.000000 0.00 0.01 0.000000 0.030000 0.010000 0.000000 0.00 0.01 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.000000 0.000000 0.01 0.01 0.00 0.00 0.030000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00000 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.08 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.010000 0.000000 0.01 0.050000 0.03 0.00 0.02 0.00 0.010000 0.00 0.000000 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.010000 0.010000 0.020000 0.000000 0.000000 0.01 0.000000 0.02 0.01 0.000000 0.000000 0.000000 0.070000 0.01 0.01 0.000000 0.00 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.000000 0.02 0.01 0.00 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.000000 0.010000 0.000000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.030000 0.000000 0.00 0.02 0.010000 0.00 0.01 0.000000 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.010000 0.03 0.000000 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.00 0.010000 0.01 0.010000 0.000000 0.01 0.000000 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.000000 0.00 0.010000 0.00 0.00 0.00 0.010000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.010000 0.00 0.00 0.01 0.000000 0.02 0.000000 0.00 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
5 US Open 0.010000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.030000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.010000 0.010000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00 0.00 0.01 0.000000 0.00 0.05000 0.02 0.010000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.01 0.01 0.010000 0.000000 0.000000 0.000000 0.00 0.020000 0.00 0.00 0.00 0.00 0.010000 0.01 0.020000 0.000000 0.00 0.01 0.00 0.010000 0.00 0.00 0.00 0.110000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.020000 0.000000 0.00 0.00 0.020000 0.01 0.00 0.010000 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.040000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.010000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.030000 0.00 0.01 0.02 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.030000 0.000000 0.00 0.010000 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.05 0.22 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.00 0.000000 0.00 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
6 Wimbledon 0.000000 0.00 0.010000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.060000 0.020000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.000000 0.010000 0.000000 0.00 0.00 0.03 0.01 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.01000 0.01 0.070000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.020000 0.000000 0.00 0.00 0.000000 0.000000 0.010000 0.010000 0.00 0.000000 0.00 0.00 0.00 0.00 0.050000 0.00 0.010000 0.000000 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.010000 0.010000 0.01 0.010000 0.020000 0.000000 0.010000 0.010000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.01 0.000000 0.000000 0.00 0.00 0.020000 0.00 0.00 0.000000 0.000000 0.000000 0.020000 0.01 0.000000 0.00 0.00 0.01 0.00 0.00 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.01 0.00 0.000000 0.110000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.030000 0.020000 0.00 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.020000 0.00 0.00 0.020000 0.00 0.000000 0.000000 0.00 0.000000 0.02 0.01 0.00 0.00 0.02 0.00 0.00 0.000000 0.00 0.000000 0.01 0.01 0.00 0.010000 0.00 0.00 0.01 0.010000 0.010000 0.01 0.00 0.000000 0.00 0.00 0.000000 0.00 0.01 0.00 0.000000 0.00 0.010000 0.01 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
7 AZ 0.020202 0.00 0.000000 NaN NaN 0.00 0.010101 NaN 0.030303 0.000000 NaN NaN 0.020202 0.010101 0.030303 0.010101 0.00 0.00 NaN 0.010101 NaN NaN 0.00 NaN NaN 0.00 NaN NaN NaN 0.000000 0.070707 0.010101 0.00 NaN NaN 0.00 0.000000 NaN NaN NaN NaN 0.040404 NaN 0.00000 0.00 0.010101 NaN NaN NaN NaN 0.000000 0.010101 NaN NaN 0.020202 0.000000 NaN 0.00 0.000000 0.010101 0.000000 0.000000 NaN 0.000000 NaN 0.00 NaN NaN 0.000000 0.00 0.000000 0.000000 0.00 NaN NaN 0.000000 NaN NaN 0.00 0.000000 0.000000 NaN 0.010101 0.010101 0.020202 0.000000 0.010101 NaN 0.010101 0.00 NaN 0.000000 0.000000 0.000000 0.000000 0.00 NaN 0.010101 NaN NaN 0.020202 NaN 0.00 NaN NaN NaN 0.010101 0.00 NaN 0.00 0.000000 0.010101 0.00 NaN NaN NaN 0.030303 0.010101 NaN 0.00 0.000000 NaN 0.00 0.000000 0.000000 0.010101 0.000000 NaN 0.010101 NaN NaN NaN NaN NaN 0.010101 0.000000 0.000000 NaN NaN 0.000000 0.00 NaN 0.010101 0.000000 0.00 0.00 0.00 NaN 0.00 NaN NaN NaN NaN NaN NaN NaN 0.000000 0.00 0.010101 0.00 NaN NaN 0.030303 0.010101 NaN NaN NaN NaN NaN NaN 0.00 NaN 0.000000 NaN 0.00 0.000000 NaN 0.000000 0.010101 NaN 0.000000 NaN NaN NaN NaN NaN NaN 0.00 0.010101 NaN 0.010101 NaN NaN 0.00 0.010101 0.00 0.00 NaN 0.000000 0.000000 NaN NaN 0.000000 NaN NaN 0.010101 NaN NaN NaN 0.000000 NaN 0.000000 NaN 0.000000 0.00 0.00 0.00 0.020202 0.000000 0.00 0.00 0.010101 0.00 0.00 0.040404 0.020202 0.000000 0.000000 0.010101 0.020202 0.010101 0.000000 0.000000 0.010101 0.010101 0.00 0.00 0.010101 0.00 0.010101 0.00 0.00 0.010101 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010101 0.010101 0.010101 0.010101 0.010101 0.000000 0.00 0.010101 0.00 0.010101 0.010101 0.000000 0.010101 0.010101 0.010101 0.010101 0.000000 0.000000 0.00 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.010101 0.00
8 CA 0.000000 0.00 0.016393 NaN NaN 0.00 0.000000 NaN 0.032787 0.000000 NaN NaN 0.000000 0.032787 0.000000 0.000000 0.00 0.00 NaN 0.000000 NaN NaN 0.00 NaN NaN 0.00 NaN NaN NaN 0.000000 0.065574 0.000000 0.00 NaN NaN 0.00 0.032787 NaN NaN NaN NaN 0.016393 NaN 0.04918 0.00 0.000000 NaN NaN NaN NaN 0.000000 0.000000 NaN NaN 0.016393 0.032787 NaN 0.00 0.016393 0.000000 0.032787 0.016393 NaN 0.000000 NaN 0.00 NaN NaN 0.016393 0.00 0.000000 0.000000 0.00 NaN NaN 0.000000 NaN NaN 0.00 0.016393 0.000000 NaN 0.000000 0.016393 0.016393 0.032787 0.000000 NaN 0.000000 0.00 NaN 0.000000 0.000000 0.000000 0.016393 0.00 NaN 0.016393 NaN NaN 0.000000 NaN 0.00 NaN NaN NaN 0.016393 0.00 NaN 0.00 0.000000 0.000000 0.00 NaN NaN NaN 0.032787 0.000000 NaN 0.00 0.032787 NaN 0.00 0.000000 0.000000 0.000000 0.016393 NaN 0.000000 NaN NaN NaN NaN NaN 0.000000 0.000000 0.000000 NaN NaN 0.032787 0.00 NaN 0.016393 0.000000 0.00 0.00 0.00 NaN 0.00 NaN NaN NaN NaN NaN NaN NaN 0.000000 0.00 0.000000 0.00 NaN NaN 0.032787 0.000000 NaN NaN NaN NaN NaN NaN 0.00 NaN 0.000000 NaN 0.00 0.016393 NaN 0.032787 0.000000 NaN 0.000000 NaN NaN NaN NaN NaN NaN 0.00 0.000000 NaN 0.000000 NaN NaN 0.00 0.000000 0.00 0.00 NaN 0.000000 0.000000 NaN NaN 0.000000 NaN NaN 0.016393 NaN NaN NaN 0.000000 NaN 0.016393 NaN 0.000000 0.00 0.00 0.00 0.000000 0.032787 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.032787 0.000000 0.016393 0.000000 0.000000 0.016393 0.016393 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.016393 0.00 0.032787 0.00 0.000000 0.000000 0.016393 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.016393 0.000000 0.000000 0.000000 0.000000 0.000000 0.016393 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
9 FL 0.020000 0.01 0.000000 NaN NaN 0.00 0.000000 NaN 0.000000 0.000000 NaN NaN 0.000000 0.010000 0.000000 0.000000 0.00 0.12 NaN 0.000000 NaN NaN 0.03 NaN NaN 0.01 NaN NaN NaN 0.000000 0.000000 0.010000 0.00 NaN NaN 0.00 0.040000 NaN NaN NaN NaN 0.010000 NaN 0.00000 0.00 0.010000 NaN NaN NaN NaN 0.000000 0.000000 NaN NaN 0.000000 0.000000 NaN 0.02 0.000000 0.010000 0.000000 0.000000 NaN 0.000000 NaN 0.00 NaN NaN 0.000000 0.01 0.000000 0.000000 0.01 NaN NaN 0.000000 NaN NaN 0.03 0.010000 0.000000 NaN 0.000000 0.000000 0.000000 0.010000 0.000000 NaN 0.000000 0.01 NaN 0.000000 0.000000 0.000000 0.000000 0.00 NaN 0.000000 NaN NaN 0.000000 NaN 0.00 NaN NaN NaN 0.010000 0.00 NaN 0.01 0.000000 0.000000 0.01 NaN NaN NaN 0.000000 0.000000 NaN 0.00 0.000000 NaN 0.00 0.000000 0.000000 0.000000 0.030000 NaN 0.030000 NaN NaN NaN NaN NaN 0.010000 0.000000 0.000000 NaN NaN 0.000000 0.00 NaN 0.000000 0.000000 0.00 0.00 0.00 NaN 0.01 NaN NaN NaN NaN NaN NaN NaN 0.050000 0.02 0.000000 0.00 NaN NaN 0.010000 0.010000 NaN NaN NaN NaN NaN NaN 0.01 NaN 0.010000 NaN 0.00 0.000000 NaN 0.010000 0.000000 NaN 0.000000 NaN NaN NaN NaN NaN NaN 0.00 0.000000 NaN 0.000000 NaN NaN 0.01 0.000000 0.05 0.02 NaN 0.000000 0.000000 NaN NaN 0.000000 NaN NaN 0.000000 NaN NaN NaN 0.000000 NaN 0.000000 NaN 0.000000 0.00 0.00 0.01 0.000000 0.000000 0.01 0.00 0.000000 0.00 0.01 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.01 0.01 0.000000 0.00 0.010000 0.00 0.01 0.020000 0.000000 0.00 0.000000 0.01 0.000000 0.010000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.01 0.000000 0.00 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.010000 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.01 0.00 0.000000 0.00
10 MA 0.000000 0.00 0.000000 NaN NaN 0.00 0.012048 NaN 0.000000 0.012048 NaN NaN 0.000000 0.000000 0.120482 0.000000 0.00 0.00 NaN 0.000000 NaN NaN 0.00 NaN NaN 0.00 NaN NaN NaN 0.012048 0.000000 0.000000 0.00 NaN NaN 0.00 0.000000 NaN NaN NaN NaN 0.000000 NaN 0.00000 0.00 0.000000 NaN NaN NaN NaN 0.012048 0.000000 NaN NaN 0.012048 0.000000 NaN 0.00 0.000000 0.000000 0.000000 0.012048 NaN 0.024096 NaN 0.00 NaN NaN 0.000000 0.00 0.012048 0.012048 0.00 NaN NaN 0.012048 NaN NaN 0.00 0.060241 0.012048 NaN 0.000000 0.012048 0.012048 0.000000 0.000000 NaN 0.000000 0.00 NaN 0.072289 0.036145 0.012048 0.000000 0.00 NaN 0.000000 NaN NaN 0.000000 NaN 0.00 NaN NaN NaN 0.000000 0.00 NaN 0.00 0.036145 0.000000 0.00 NaN NaN NaN 0.000000 0.000000 NaN 0.00 0.000000 NaN 0.00 0.012048 0.012048 0.000000 0.000000 NaN 0.000000 NaN NaN NaN NaN NaN 0.000000 0.012048 0.012048 NaN NaN 0.000000 0.00 NaN 0.024096 0.108434 0.00 0.00 0.00 NaN 0.00 NaN NaN NaN NaN NaN NaN NaN 0.012048 0.00 0.000000 0.00 NaN NaN 0.000000 0.000000 NaN NaN NaN NaN NaN NaN 0.00 NaN 0.024096 NaN 0.00 0.000000 NaN 0.024096 0.000000 NaN 0.024096 NaN NaN NaN NaN NaN NaN 0.00 0.000000 NaN 0.000000 NaN NaN 0.00 0.000000 0.00 0.00 NaN 0.012048 0.012048 NaN NaN 0.012048 NaN NaN 0.000000 NaN NaN NaN 0.012048 NaN 0.000000 NaN 0.012048 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.012048 0.000000 0.000000 0.012048 0.000000 0.012048 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.012048 0.024096 0.000000 0.012048 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
11 OH 0.020000 0.00 0.000000 NaN NaN 0.00 0.000000 NaN 0.000000 0.000000 NaN NaN 0.000000 0.000000 0.000000 0.000000 0.00 0.00 NaN 0.000000 NaN NaN 0.00 NaN NaN 0.00 NaN NaN NaN 0.000000 0.010000 0.000000 0.00 NaN NaN 0.01 0.020000 NaN NaN NaN NaN 0.000000 NaN 0.01000 0.02 0.010000 NaN NaN NaN NaN 0.000000 0.010000 NaN NaN 0.000000 0.000000 NaN 0.00 0.000000 0.000000 0.000000 0.000000 NaN 0.020000 NaN 0.01 NaN NaN 0.000000 0.00 0.000000 0.000000 0.00 NaN NaN 0.000000 NaN NaN 0.00 0.030000 0.010000 NaN 0.010000 0.000000 0.000000 0.000000 0.000000 NaN 0.000000 0.00 NaN 0.000000 0.000000 0.000000 0.000000 0.00 NaN 0.010000 NaN NaN 0.000000 NaN 0.01 NaN NaN NaN 0.000000 0.00 NaN 0.00 0.010000 0.000000 0.00 NaN NaN NaN 0.000000 0.010000 NaN 0.01 0.000000 NaN 0.01 0.000000 0.000000 0.000000 0.040000 NaN 0.000000 NaN NaN NaN NaN NaN 0.010000 0.030000 0.000000 NaN NaN 0.000000 0.03 NaN 0.010000 0.000000 0.00 0.01 0.01 NaN 0.00 NaN NaN NaN NaN NaN NaN NaN 0.020000 0.00 0.010000 0.00 NaN NaN 0.010000 0.010000 NaN NaN NaN NaN NaN NaN 0.00 NaN 0.010000 NaN 0.01 0.000000 NaN 0.000000 0.000000 NaN 0.000000 NaN NaN NaN NaN NaN NaN 0.00 0.000000 NaN 0.000000 NaN NaN 0.00 0.000000 0.11 0.04 NaN 0.000000 0.000000 NaN NaN 0.000000 NaN NaN 0.000000 NaN NaN NaN 0.000000 NaN 0.000000 NaN 0.000000 0.01 0.00 0.01 0.000000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.020000 0.01 0.03 0.000000 0.000000 0.02 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.010000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.07 0.05 0.000000 0.00 0.01 0.000000 0.06
12 TX 0.010000 0.03 0.000000 NaN NaN 0.01 0.000000 NaN 0.000000 0.000000 NaN NaN 0.000000 0.000000 0.090000 0.020000 0.01 0.00 NaN 0.000000 NaN NaN 0.00 NaN NaN 0.00 NaN NaN NaN 0.000000 0.020000 0.010000 0.01 NaN NaN 0.00 0.000000 NaN NaN NaN NaN 0.000000 NaN 0.03000 0.02 0.000000 NaN NaN NaN NaN 0.010000 0.010000 NaN NaN 0.000000 0.010000 NaN 0.00 0.000000 0.000000 0.000000 0.000000 NaN 0.060000 NaN 0.00 NaN NaN 0.010000 0.00 0.000000 0.000000 0.01 NaN NaN 0.000000 NaN NaN 0.01 0.010000 0.000000 NaN 0.000000 0.000000 0.000000 0.000000 0.000000 NaN 0.000000 0.00 NaN 0.010000 0.000000 0.000000 0.010000 0.01 NaN 0.000000 NaN NaN 0.030000 NaN 0.01 NaN NaN NaN 0.000000 0.01 NaN 0.00 0.070000 0.000000 0.00 NaN NaN NaN 0.000000 0.000000 NaN 0.02 0.000000 NaN 0.00 0.000000 0.010000 0.000000 0.050000 NaN 0.010000 NaN NaN NaN NaN NaN 0.000000 0.060000 0.000000 NaN NaN 0.010000 0.00 NaN 0.010000 0.000000 0.02 0.00 0.00 NaN 0.00 NaN NaN NaN NaN NaN NaN NaN 0.050000 0.01 0.000000 0.01 NaN NaN 0.000000 0.000000 NaN NaN NaN NaN NaN NaN 0.00 NaN 0.000000 NaN 0.00 0.000000 NaN 0.020000 0.070000 NaN 0.010000 NaN NaN NaN NaN NaN NaN 0.01 0.000000 NaN 0.000000 NaN NaN 0.01 0.000000 0.00 0.00 NaN 0.000000 0.000000 NaN NaN 0.000000 NaN NaN 0.000000 NaN NaN NaN 0.000000 NaN 0.000000 NaN 0.000000 0.00 0.01 0.00 0.000000 0.000000 0.00 0.01 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.01 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00

Printing out the size of the concatenated DF:

(13, 281)

This implies that the above dataframe contains 13 unique Tennis event destinations which amount to an aggregate of 281 unique venue categories, among the 13 destinations. The 13 different Tennis event destinations are clustered against one another through computing the common venue categories shared between the different destinations (i.e. the venue categories similarity between any 2 given neighborhoods)

Cleaining the DF and replacing all 'NaN' with value of '0' to run the clustering algorithm:

Event_Venue American Restaurant Art Gallery Arts & Crafts Store Arts & Entertainment Asian Restaurant Athletics & Sports Auditorium Australian Restaurant Automotive Shop BBQ Joint Baby Store Bagel Shop Bakery Bank Bar Basketball Court Basketball Stadium Beach Beer Bar Beer Garden Bike Rental / Bike Share Bistro Boat or Ferry Bookstore Botanical Garden Boutique Brewery Bridal Shop Bridge Buffet Building Burger Joint Bus Line Bus Station Bus Stop Business Center Café Camera Store Candy Store Casino Chinese Restaurant Church Circus Clothing Store Cocktail Bar Coffee Shop College Baseball Diamond College Classroom College Stadium Comedy Club Concert Hall Conference Room Convention Center Corporate Cafeteria Cosmetics Shop Coworking Space Creperie Cuban Restaurant Deli / Bodega Diner Doctor's Office Donut Shop Eastern European Restaurant Event Space Exhibit Factory Fair Farm Fast Food Restaurant Food & Drink Shop Food Court Food Service Food Truck Fountain French Restaurant Fried Chicken Joint Furniture / Home Store Garden Gas Station General Entertainment Gift Shop Gourmet Shop Government Building Grocery Store Gym Gym / Fitness Center Hardware Store Health & Beauty Service High School Historic Site History Museum Hockey Arena Hockey Field Hot Dog Joint Hotel Hotel Bar Hotel Pool Ice Cream Shop Indian Restaurant Indoor Play Area Italian Restaurant Jewelry Store Juice Bar Karaoke Bar Kitchen Supply Store Korean Restaurant Laundry Service Light Rail Station Lingerie Store Liquor Store Lounge Massage Studio Mediterranean Restaurant Meeting Room Men's Store Metro Station Mexican Restaurant Middle School Mini Golf Miscellaneous Shop Mobile Phone Shop Monument / Landmark Movie Theater Museum Music Venue Nightclub Office Optical Shop Other Great Outdoors Other Repair Shop Outdoor Event Space Outdoor Sculpture Outdoors & Recreation Paper / Office Supplies Store Park Parking Performing Arts Venue Perfume Shop Pet Store Pharmacy Photography Lab Physical Therapist Pizza Place Platform Plaza Police Station Pool Pool Hall Post Office Pub Public Art Public Bathroom Real Estate Office Recreation Center Recycling Facility Rental Car Location Residential Building (Apartment / Condo) Restaurant Rock Club Roof Deck Rugby Stadium Salad Place Salon / Barbershop Sandwich Place Scenic Lookout Sculpture Garden Seafood Restaurant Shoe Repair Shoe Store Shopping Plaza Skating Rink Smoke Shop Snack Place Soccer Stadium Souvenir Shop Spa Sporting Event Sporting Goods Shop Sports Bar Sports Club Stadium Stationery Store Steakhouse Strip Club Supermarket Sushi Restaurant Swiss Restaurant TV Station Taco Place Tailor Shop Tattoo Parlor Taxi Stand Tea Room Tech Startup Temple Tennis Court Tennis Stadium Toy / Game Store Train Station Tram Station Transportation Service Travel Lounge University Vacation Rental Vegetarian / Vegan Restaurant Video Store Warehouse Warehouse Store Whisky Bar Wine Bar Wine Shop Women's Store Yoga Studio ATM Accessories Store Advertising Agency Arcade Baseball Field Big Box Store Bike Shop Business Service Capitol Building Comfort Food Restaurant Construction & Landscaping Convenience Store Dentist's Office Department Store Dessert Shop Discount Store Dive Bar Dog Run EV Charging Station Electronics Store Fabric Shop Field Fire Station Fish & Chips Shop Food Gastropub General Travel German Restaurant Golf Course Harbor / Marina Hospital Housing Development Kids Store Latin American Restaurant Market Moving Target Nail Salon Newsstand Nightlife Spot Non-Profit Other Nightlife Peruvian Restaurant Pet Service Planetarium Playground Preschool Professional & Other Places Radio Station River School Shopping Mall Skate Park Soccer Field Speakeasy Storage Facility Student Center Supplement Shop Surf Spot Thai Restaurant Theater Theme Park Theme Park Ride / Attraction Thrift / Vintage Store Toll Booth Tourist Information Center Trail Water Park
0 Aus Open 0.000000 0.00 0.000000 0.00 0.01 0.00 0.010000 0.02 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.020000 0.000000 0.00 0.00 0.00 0.020000 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.02 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.00 0.040000 0.01 0.00 0.00 0.00 0.000000 0.00 0.01000 0.00 0.010000 0.01 0.00 0.00 0.00 0.030000 0.010000 0.01 0.00 0.000000 0.020000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.150000 0.00 0.00 0.00 0.00 0.000000 0.02 0.000000 0.020000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.050000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.01 0.00 0.01 0.010000 0.000000 0.00 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.010000 0.000000 0.020000 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.01 0.000000 0.00 0.000000 0.010000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.02 0.00 0.000000 0.05 0.13 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.06 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
1 French Open 0.000000 0.01 0.000000 0.05 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.000000 0.020000 0.000000 0.02 0.00 0.02 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00000 0.00 0.000000 0.00 0.04 0.01 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.030000 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.04 0.000000 0.00 0.02 0.02 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.010000 0.000000 0.00 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.030000 0.00 0.020000 0.00 0.00 0.00 0.01 0.00 0.010000 0.010000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.000000 0.02 0.010000 0.01 0.01 0.00 0.000000 0.020000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.000000 0.01 0.00 0.010000 0.00 0.030000 0.000000 0.01 0.070000 0.00 0.00 0.00 0.02 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.17 0.02 0.00 0.000000 0.000000 0.00 0.01 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
2 Rod_Laver_Chicago 0.010000 0.00 0.000000 0.01 0.00 0.00 0.000000 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.090000 0.010000 0.05 0.00 0.01 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.000000 0.000000 0.010000 0.03 0.01 0.02 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.02 0.01000 0.00 0.010000 0.00 0.00 0.00 0.00 0.020000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.00 0.00 0.00 0.01 0.000000 0.00 0.010000 0.000000 0.01 0.00 0.00 0.020000 0.00 0.00 0.00 0.060000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.00 0.040000 0.000000 0.020000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.01 0.000000 0.020000 0.000000 0.010000 0.00 0.000000 0.00 0.00 0.06 0.00 0.00 0.000000 0.040000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.02 0.010000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.000000 0.00 0.00 0.000000 0.00 0.030000 0.040000 0.00 0.080000 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.010000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.02 0.000000 0.00 0.00 0.01 0.010000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
3 Rod_Laver_Czech 0.000000 0.01 0.010000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.02 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.010000 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.010000 0.010000 0.000000 0.00 0.00 0.00 0.00 0.010000 0.00 0.01 0.01 0.00 0.000000 0.00 0.08000 0.01 0.000000 0.00 0.00 0.00 0.01 0.000000 0.000000 0.01 0.01 0.020000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.00 0.01 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.020000 0.010000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.010000 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.01 0.000000 0.02 0.00 0.01 0.01 0.00 0.010000 0.00 0.03 0.00 0.140000 0.000000 0.00 0.02 0.01 0.00 0.000000 0.000000 0.01 0.01 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.020000 0.00 0.010000 0.01 0.00 0.00 0.00 0.01 0.000000 0.000000 0.000000 0.01 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 0.010000 0.02 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.03 0.00 0.03 0.00 0.000000 0.00 0.00 0.000000 0.00 0.040000 0.010000 0.00 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.01 0.000000 0.01 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.030000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
4 Rod_Laver_Swizz 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.00 0.010000 0.000000 0.00 0.01 0.000000 0.030000 0.010000 0.000000 0.00 0.01 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.000000 0.000000 0.01 0.01 0.00 0.00 0.030000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00000 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.08 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.010000 0.000000 0.01 0.050000 0.03 0.00 0.02 0.00 0.010000 0.00 0.000000 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.010000 0.010000 0.020000 0.000000 0.000000 0.01 0.000000 0.02 0.01 0.000000 0.000000 0.000000 0.070000 0.01 0.01 0.000000 0.00 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.000000 0.02 0.01 0.00 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.000000 0.010000 0.000000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.030000 0.000000 0.00 0.02 0.010000 0.00 0.01 0.000000 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.010000 0.03 0.000000 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.00 0.010000 0.01 0.010000 0.000000 0.01 0.000000 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.000000 0.00 0.010000 0.00 0.00 0.00 0.010000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.010000 0.00 0.00 0.01 0.000000 0.02 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
5 US Open 0.010000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.030000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.010000 0.010000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00 0.00 0.01 0.000000 0.00 0.05000 0.02 0.010000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.01 0.01 0.010000 0.000000 0.000000 0.000000 0.00 0.020000 0.00 0.00 0.00 0.00 0.010000 0.01 0.020000 0.000000 0.00 0.01 0.00 0.010000 0.00 0.00 0.00 0.110000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.020000 0.000000 0.00 0.00 0.020000 0.01 0.00 0.010000 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.040000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.010000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.030000 0.00 0.01 0.02 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.030000 0.000000 0.00 0.010000 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.05 0.22 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
6 Wimbledon 0.000000 0.00 0.010000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.060000 0.020000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.000000 0.010000 0.000000 0.00 0.00 0.03 0.01 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.01000 0.01 0.070000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.020000 0.000000 0.00 0.00 0.000000 0.000000 0.010000 0.010000 0.00 0.000000 0.00 0.00 0.00 0.00 0.050000 0.00 0.010000 0.000000 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.010000 0.010000 0.01 0.010000 0.020000 0.000000 0.010000 0.010000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.01 0.000000 0.000000 0.00 0.00 0.020000 0.00 0.00 0.000000 0.000000 0.000000 0.020000 0.01 0.000000 0.00 0.00 0.01 0.00 0.00 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.01 0.00 0.000000 0.110000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.030000 0.020000 0.00 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.020000 0.00 0.00 0.020000 0.00 0.000000 0.000000 0.00 0.000000 0.02 0.01 0.00 0.00 0.02 0.00 0.00 0.000000 0.00 0.000000 0.01 0.01 0.00 0.010000 0.00 0.00 0.01 0.010000 0.010000 0.01 0.00 0.000000 0.00 0.00 0.000000 0.00 0.01 0.00 0.000000 0.00 0.010000 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
7 AZ 0.020202 0.00 0.000000 0.00 0.00 0.00 0.010101 0.00 0.030303 0.000000 0.00 0.00 0.020202 0.010101 0.030303 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.070707 0.010101 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.040404 0.00 0.00000 0.00 0.010101 0.00 0.00 0.00 0.00 0.000000 0.010101 0.00 0.00 0.020202 0.000000 0.00 0.00 0.000000 0.010101 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.010101 0.010101 0.020202 0.000000 0.010101 0.00 0.010101 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010101 0.00 0.00 0.020202 0.00 0.00 0.00 0.00 0.00 0.010101 0.00 0.00 0.00 0.000000 0.010101 0.00 0.00 0.00 0.00 0.030303 0.010101 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.010101 0.000000 0.00 0.010101 0.00 0.00 0.00 0.00 0.00 0.010101 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010101 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.010101 0.00 0.00 0.00 0.030303 0.010101 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.010101 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.010101 0.00 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010101 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.020202 0.000000 0.00 0.00 0.010101 0.00 0.00 0.040404 0.020202 0.000000 0.000000 0.010101 0.020202 0.010101 0.000000 0.000000 0.010101 0.010101 0.00 0.00 0.010101 0.00 0.010101 0.00 0.00 0.010101 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010101 0.010101 0.010101 0.010101 0.010101 0.000000 0.00 0.010101 0.00 0.010101 0.010101 0.000000 0.010101 0.010101 0.010101 0.010101 0.000000 0.000000 0.00 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.010101 0.00
8 CA 0.000000 0.00 0.016393 0.00 0.00 0.00 0.000000 0.00 0.032787 0.000000 0.00 0.00 0.000000 0.032787 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.065574 0.000000 0.00 0.00 0.00 0.00 0.032787 0.00 0.00 0.00 0.00 0.016393 0.00 0.04918 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.016393 0.032787 0.00 0.00 0.016393 0.000000 0.032787 0.016393 0.00 0.000000 0.00 0.00 0.00 0.00 0.016393 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.016393 0.000000 0.00 0.000000 0.016393 0.016393 0.032787 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.016393 0.00 0.00 0.016393 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.016393 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.032787 0.000000 0.00 0.00 0.032787 0.00 0.00 0.000000 0.000000 0.000000 0.016393 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.000000 0.000000 0.00 0.00 0.032787 0.00 0.00 0.016393 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.032787 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.016393 0.00 0.032787 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.016393 0.00 0.00 0.00 0.000000 0.00 0.016393 0.00 0.000000 0.00 0.00 0.00 0.000000 0.032787 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.032787 0.000000 0.016393 0.000000 0.000000 0.016393 0.016393 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.016393 0.00 0.032787 0.00 0.000000 0.000000 0.016393 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.016393 0.000000 0.000000 0.000000 0.000000 0.000000 0.016393 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
9 FL 0.020000 0.01 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.000000 0.00 0.12 0.00 0.000000 0.00 0.00 0.03 0.00 0.00 0.01 0.00 0.00 0.00 0.000000 0.000000 0.010000 0.00 0.00 0.00 0.00 0.040000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00000 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.02 0.000000 0.010000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.01 0.000000 0.000000 0.01 0.00 0.00 0.000000 0.00 0.00 0.03 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.010000 0.000000 0.00 0.000000 0.01 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.010000 0.00 0.00 0.01 0.000000 0.000000 0.01 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.030000 0.00 0.030000 0.00 0.00 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.050000 0.02 0.000000 0.00 0.00 0.00 0.010000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.010000 0.00 0.00 0.000000 0.00 0.010000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.01 0.000000 0.05 0.02 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.01 0.000000 0.000000 0.01 0.00 0.000000 0.00 0.01 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.01 0.01 0.000000 0.00 0.010000 0.00 0.01 0.020000 0.000000 0.00 0.000000 0.01 0.000000 0.010000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.01 0.000000 0.00 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.010000 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.01 0.00 0.000000 0.00
10 MA 0.000000 0.00 0.000000 0.00 0.00 0.00 0.012048 0.00 0.000000 0.012048 0.00 0.00 0.000000 0.000000 0.120482 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.012048 0.000000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00000 0.00 0.000000 0.00 0.00 0.00 0.00 0.012048 0.000000 0.00 0.00 0.012048 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.012048 0.00 0.024096 0.00 0.00 0.00 0.00 0.000000 0.00 0.012048 0.012048 0.00 0.00 0.00 0.012048 0.00 0.00 0.00 0.060241 0.012048 0.00 0.000000 0.012048 0.012048 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.072289 0.036145 0.012048 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.036145 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.012048 0.012048 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.012048 0.012048 0.00 0.00 0.000000 0.00 0.00 0.024096 0.108434 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.012048 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.024096 0.00 0.00 0.000000 0.00 0.024096 0.000000 0.00 0.024096 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.012048 0.012048 0.00 0.00 0.012048 0.00 0.00 0.000000 0.00 0.00 0.00 0.012048 0.00 0.000000 0.00 0.012048 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.012048 0.000000 0.000000 0.012048 0.000000 0.012048 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.012048 0.024096 0.000000 0.012048 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
11 OH 0.020000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.010000 0.000000 0.00 0.00 0.00 0.01 0.020000 0.00 0.00 0.00 0.00 0.000000 0.00 0.01000 0.02 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.020000 0.00 0.01 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.030000 0.010000 0.00 0.010000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.01 0.000000 0.00 0.01 0.000000 0.000000 0.000000 0.040000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.010000 0.030000 0.000000 0.00 0.00 0.000000 0.03 0.00 0.010000 0.000000 0.00 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.020000 0.00 0.010000 0.00 0.00 0.00 0.010000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.010000 0.00 0.01 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.11 0.04 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.01 0.00 0.01 0.000000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.020000 0.01 0.03 0.000000 0.000000 0.02 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.010000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.07 0.05 0.000000 0.00 0.01 0.000000 0.06
12 TX 0.010000 0.03 0.000000 0.00 0.00 0.01 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.090000 0.020000 0.01 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.020000 0.010000 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.03000 0.02 0.000000 0.00 0.00 0.00 0.00 0.010000 0.010000 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.060000 0.00 0.00 0.00 0.00 0.010000 0.00 0.000000 0.000000 0.01 0.00 0.00 0.000000 0.00 0.00 0.01 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.010000 0.01 0.00 0.000000 0.00 0.00 0.030000 0.00 0.01 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.070000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.02 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.050000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.060000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.010000 0.000000 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.050000 0.01 0.000000 0.01 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.020000 0.070000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.01 0.00 0.000000 0.000000 0.00 0.01 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.01 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00

Determing the optimal number of clusters to initate to classify the 6 candidate locations using 'Elbow Method' and 'Silhoutte Method':

[ 2  3  4  5  6  7  8  9 10 11] [0.11791793236653304, 0.12470947616876156, 0.12194144381406706, 0.11199609810981329, 0.09673824559027976, 0.07359790512081775, 0.056653659471948545, 0.061144107701112574, 0.050284327439997986, 0.03430166590086462]

Using the resulst of the 'Silhoutte Method (number of clusters with highest score)', 4 clusters were chosen to execute the 'KMeans' algorithm (Although the graph peaks at 3, there is a marginal drop in the Silhoutte score when cluster size varies from 3 to 4 clusters):

array([1, 2, 3, 0, 0, 1, 0, 0, 0, 2, 3, 2, 3])
Cluster_Labels Event_Venue American Restaurant Art Gallery Arts & Crafts Store Arts & Entertainment Asian Restaurant Athletics & Sports Auditorium Australian Restaurant Automotive Shop BBQ Joint Baby Store Bagel Shop Bakery Bank Bar Basketball Court Basketball Stadium Beach Beer Bar Beer Garden Bike Rental / Bike Share Bistro Boat or Ferry Bookstore Botanical Garden Boutique Brewery Bridal Shop Bridge Buffet Building Burger Joint Bus Line Bus Station Bus Stop Business Center Café Camera Store Candy Store Casino Chinese Restaurant Church Circus Clothing Store Cocktail Bar Coffee Shop College Baseball Diamond College Classroom College Stadium Comedy Club Concert Hall Conference Room Convention Center Corporate Cafeteria Cosmetics Shop Coworking Space Creperie Cuban Restaurant Deli / Bodega Diner Doctor's Office Donut Shop Eastern European Restaurant Event Space Exhibit Factory Fair Farm Fast Food Restaurant Food & Drink Shop Food Court Food Service Food Truck Fountain French Restaurant Fried Chicken Joint Furniture / Home Store Garden Gas Station General Entertainment Gift Shop Gourmet Shop Government Building Grocery Store Gym Gym / Fitness Center Hardware Store Health & Beauty Service High School Historic Site History Museum Hockey Arena Hockey Field Hot Dog Joint Hotel Hotel Bar Hotel Pool Ice Cream Shop Indian Restaurant Indoor Play Area Italian Restaurant Jewelry Store Juice Bar Karaoke Bar Kitchen Supply Store Korean Restaurant Laundry Service Light Rail Station Lingerie Store Liquor Store Lounge Massage Studio Mediterranean Restaurant Meeting Room Men's Store Metro Station Mexican Restaurant Middle School Mini Golf Miscellaneous Shop Mobile Phone Shop Monument / Landmark Movie Theater Museum Music Venue Nightclub Office Optical Shop Other Great Outdoors Other Repair Shop Outdoor Event Space Outdoor Sculpture Outdoors & Recreation Paper / Office Supplies Store Park Parking Performing Arts Venue Perfume Shop Pet Store Pharmacy Photography Lab Physical Therapist Pizza Place Platform Plaza Police Station Pool Pool Hall Post Office Pub Public Art Public Bathroom Real Estate Office Recreation Center Recycling Facility Rental Car Location Residential Building (Apartment / Condo) Restaurant Rock Club Roof Deck Rugby Stadium Salad Place Salon / Barbershop Sandwich Place Scenic Lookout Sculpture Garden Seafood Restaurant Shoe Repair Shoe Store Shopping Plaza Skating Rink Smoke Shop Snack Place Soccer Stadium Souvenir Shop Spa Sporting Event Sporting Goods Shop Sports Bar Sports Club Stadium Stationery Store Steakhouse Strip Club Supermarket Sushi Restaurant Swiss Restaurant TV Station Taco Place Tailor Shop Tattoo Parlor Taxi Stand Tea Room Tech Startup Temple Tennis Court Tennis Stadium Toy / Game Store Train Station Tram Station Transportation Service Travel Lounge University Vacation Rental Vegetarian / Vegan Restaurant Video Store Warehouse Warehouse Store Whisky Bar Wine Bar Wine Shop Women's Store Yoga Studio ATM Accessories Store Advertising Agency Arcade Baseball Field Big Box Store Bike Shop Business Service Capitol Building Comfort Food Restaurant Construction & Landscaping Convenience Store Dentist's Office Department Store Dessert Shop Discount Store Dive Bar Dog Run EV Charging Station Electronics Store Fabric Shop Field Fire Station Fish & Chips Shop Food Gastropub General Travel German Restaurant Golf Course Harbor / Marina Hospital Housing Development Kids Store Latin American Restaurant Market Moving Target Nail Salon Newsstand Nightlife Spot Non-Profit Other Nightlife Peruvian Restaurant Pet Service Planetarium Playground Preschool Professional & Other Places Radio Station River School Shopping Mall Skate Park Soccer Field Speakeasy Storage Facility Student Center Supplement Shop Surf Spot Thai Restaurant Theater Theme Park Theme Park Ride / Attraction Thrift / Vintage Store Toll Booth Tourist Information Center Trail Water Park
0 1 Aus Open 0.000000 0.00 0.000000 0.00 0.01 0.00 0.010000 0.02 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.020000 0.000000 0.00 0.00 0.00 0.020000 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.02 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.00 0.040000 0.01 0.00 0.00 0.00 0.000000 0.00 0.01000 0.00 0.010000 0.01 0.00 0.00 0.00 0.030000 0.010000 0.01 0.00 0.000000 0.020000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.150000 0.00 0.00 0.00 0.00 0.000000 0.02 0.000000 0.020000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.050000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.01 0.00 0.01 0.010000 0.000000 0.00 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.010000 0.000000 0.020000 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.01 0.000000 0.00 0.000000 0.010000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.02 0.00 0.000000 0.05 0.13 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.06 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
1 2 French Open 0.000000 0.01 0.000000 0.05 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.000000 0.020000 0.000000 0.02 0.00 0.02 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00000 0.00 0.000000 0.00 0.04 0.01 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.030000 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.04 0.000000 0.00 0.02 0.02 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.010000 0.000000 0.00 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.030000 0.00 0.020000 0.00 0.00 0.00 0.01 0.00 0.010000 0.010000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.000000 0.02 0.010000 0.01 0.01 0.00 0.000000 0.020000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.000000 0.01 0.00 0.010000 0.00 0.030000 0.000000 0.01 0.070000 0.00 0.00 0.00 0.02 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.17 0.02 0.00 0.000000 0.000000 0.00 0.01 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
2 3 Rod_Laver_Chicago 0.010000 0.00 0.000000 0.01 0.00 0.00 0.000000 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.090000 0.010000 0.05 0.00 0.01 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.000000 0.000000 0.010000 0.03 0.01 0.02 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.02 0.01000 0.00 0.010000 0.00 0.00 0.00 0.00 0.020000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.00 0.00 0.00 0.01 0.000000 0.00 0.010000 0.000000 0.01 0.00 0.00 0.020000 0.00 0.00 0.00 0.060000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.00 0.040000 0.000000 0.020000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.01 0.000000 0.020000 0.000000 0.010000 0.00 0.000000 0.00 0.00 0.06 0.00 0.00 0.000000 0.040000 0.010000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.02 0.010000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.000000 0.00 0.00 0.000000 0.00 0.030000 0.040000 0.00 0.080000 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.010000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.02 0.000000 0.00 0.00 0.01 0.010000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
3 0 Rod_Laver_Czech 0.000000 0.01 0.010000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.02 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.010000 0.01 0.01 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.010000 0.010000 0.000000 0.00 0.00 0.00 0.00 0.010000 0.00 0.01 0.01 0.00 0.000000 0.00 0.08000 0.01 0.000000 0.00 0.00 0.00 0.01 0.000000 0.000000 0.01 0.01 0.020000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010000 0.00 0.01 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.020000 0.010000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.010000 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.01 0.000000 0.02 0.00 0.01 0.01 0.00 0.010000 0.00 0.03 0.00 0.140000 0.000000 0.00 0.02 0.01 0.00 0.000000 0.000000 0.01 0.01 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.020000 0.00 0.010000 0.01 0.00 0.00 0.00 0.01 0.000000 0.000000 0.000000 0.01 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 0.010000 0.02 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.03 0.00 0.03 0.00 0.000000 0.00 0.00 0.000000 0.00 0.040000 0.010000 0.00 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.01 0.000000 0.01 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.030000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
4 0 Rod_Laver_Swizz 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.00 0.010000 0.000000 0.00 0.01 0.000000 0.030000 0.010000 0.000000 0.00 0.01 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.000000 0.000000 0.01 0.01 0.00 0.00 0.030000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00000 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.08 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.010000 0.000000 0.01 0.050000 0.03 0.00 0.02 0.00 0.010000 0.00 0.000000 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.010000 0.010000 0.020000 0.000000 0.000000 0.01 0.000000 0.02 0.01 0.000000 0.000000 0.000000 0.070000 0.01 0.01 0.000000 0.00 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.000000 0.02 0.01 0.00 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.000000 0.010000 0.000000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.030000 0.000000 0.00 0.02 0.010000 0.00 0.01 0.000000 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.010000 0.03 0.000000 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.00 0.010000 0.01 0.010000 0.000000 0.01 0.000000 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.000000 0.00 0.010000 0.00 0.00 0.00 0.010000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.010000 0.00 0.00 0.01 0.000000 0.02 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
5 1 US Open 0.010000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.030000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.010000 0.010000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00 0.00 0.01 0.000000 0.00 0.05000 0.02 0.010000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.01 0.01 0.010000 0.000000 0.000000 0.000000 0.00 0.020000 0.00 0.00 0.00 0.00 0.010000 0.01 0.020000 0.000000 0.00 0.01 0.00 0.010000 0.00 0.00 0.00 0.110000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.020000 0.000000 0.00 0.00 0.020000 0.01 0.00 0.010000 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.040000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.010000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.030000 0.00 0.01 0.02 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.030000 0.000000 0.00 0.010000 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.05 0.22 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.020000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
6 0 Wimbledon 0.000000 0.00 0.010000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.010000 0.060000 0.020000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.000000 0.010000 0.000000 0.00 0.00 0.03 0.01 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.01000 0.01 0.070000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.020000 0.000000 0.00 0.00 0.000000 0.000000 0.010000 0.010000 0.00 0.000000 0.00 0.00 0.00 0.00 0.050000 0.00 0.010000 0.000000 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.010000 0.010000 0.01 0.010000 0.020000 0.000000 0.010000 0.010000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.01 0.000000 0.000000 0.00 0.00 0.020000 0.00 0.00 0.000000 0.000000 0.000000 0.020000 0.01 0.000000 0.00 0.00 0.01 0.00 0.00 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.01 0.00 0.000000 0.110000 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.030000 0.020000 0.00 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.020000 0.00 0.00 0.020000 0.00 0.000000 0.000000 0.00 0.000000 0.02 0.01 0.00 0.00 0.02 0.00 0.00 0.000000 0.00 0.000000 0.01 0.01 0.00 0.010000 0.00 0.00 0.01 0.010000 0.010000 0.01 0.00 0.000000 0.00 0.00 0.000000 0.00 0.01 0.00 0.000000 0.00 0.010000 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
7 0 AZ 0.020202 0.00 0.000000 0.00 0.00 0.00 0.010101 0.00 0.030303 0.000000 0.00 0.00 0.020202 0.010101 0.030303 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.070707 0.010101 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.040404 0.00 0.00000 0.00 0.010101 0.00 0.00 0.00 0.00 0.000000 0.010101 0.00 0.00 0.020202 0.000000 0.00 0.00 0.000000 0.010101 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.010101 0.010101 0.020202 0.000000 0.010101 0.00 0.010101 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010101 0.00 0.00 0.020202 0.00 0.00 0.00 0.00 0.00 0.010101 0.00 0.00 0.00 0.000000 0.010101 0.00 0.00 0.00 0.00 0.030303 0.010101 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.010101 0.000000 0.00 0.010101 0.00 0.00 0.00 0.00 0.00 0.010101 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010101 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.010101 0.00 0.00 0.00 0.030303 0.010101 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.010101 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.010101 0.00 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.010101 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.020202 0.000000 0.00 0.00 0.010101 0.00 0.00 0.040404 0.020202 0.000000 0.000000 0.010101 0.020202 0.010101 0.000000 0.000000 0.010101 0.010101 0.00 0.00 0.010101 0.00 0.010101 0.00 0.00 0.010101 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.010101 0.010101 0.010101 0.010101 0.010101 0.000000 0.00 0.010101 0.00 0.010101 0.010101 0.000000 0.010101 0.010101 0.010101 0.010101 0.000000 0.000000 0.00 0.010101 0.00 0.00 0.00 0.010101 0.00 0.00 0.010101 0.00
8 0 CA 0.000000 0.00 0.016393 0.00 0.00 0.00 0.000000 0.00 0.032787 0.000000 0.00 0.00 0.000000 0.032787 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.065574 0.000000 0.00 0.00 0.00 0.00 0.032787 0.00 0.00 0.00 0.00 0.016393 0.00 0.04918 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.016393 0.032787 0.00 0.00 0.016393 0.000000 0.032787 0.016393 0.00 0.000000 0.00 0.00 0.00 0.00 0.016393 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.016393 0.000000 0.00 0.000000 0.016393 0.016393 0.032787 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.016393 0.00 0.00 0.016393 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.016393 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.032787 0.000000 0.00 0.00 0.032787 0.00 0.00 0.000000 0.000000 0.000000 0.016393 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.000000 0.000000 0.00 0.00 0.032787 0.00 0.00 0.016393 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.032787 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.016393 0.00 0.032787 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.016393 0.00 0.00 0.00 0.000000 0.00 0.016393 0.00 0.000000 0.00 0.00 0.00 0.000000 0.032787 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.032787 0.000000 0.016393 0.000000 0.000000 0.016393 0.016393 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.016393 0.00 0.032787 0.00 0.000000 0.000000 0.016393 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.016393 0.000000 0.000000 0.000000 0.000000 0.000000 0.016393 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
9 2 FL 0.020000 0.01 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.000000 0.00 0.12 0.00 0.000000 0.00 0.00 0.03 0.00 0.00 0.01 0.00 0.00 0.00 0.000000 0.000000 0.010000 0.00 0.00 0.00 0.00 0.040000 0.00 0.00 0.00 0.00 0.010000 0.00 0.00000 0.00 0.010000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.02 0.000000 0.010000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.01 0.000000 0.000000 0.01 0.00 0.00 0.000000 0.00 0.00 0.03 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.010000 0.000000 0.00 0.000000 0.01 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.010000 0.00 0.00 0.01 0.000000 0.000000 0.01 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.030000 0.00 0.030000 0.00 0.00 0.00 0.00 0.00 0.010000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.050000 0.02 0.000000 0.00 0.00 0.00 0.010000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.010000 0.00 0.00 0.000000 0.00 0.010000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.01 0.000000 0.05 0.02 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.00 0.01 0.000000 0.000000 0.01 0.00 0.000000 0.00 0.01 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.01 0.01 0.000000 0.00 0.010000 0.00 0.01 0.020000 0.000000 0.00 0.000000 0.01 0.000000 0.010000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.01 0.000000 0.00 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.010000 0.000000 0.02 0.000000 0.00 0.00 0.01 0.000000 0.01 0.00 0.000000 0.00
10 3 MA 0.000000 0.00 0.000000 0.00 0.00 0.00 0.012048 0.00 0.000000 0.012048 0.00 0.00 0.000000 0.000000 0.120482 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.012048 0.000000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.00000 0.00 0.000000 0.00 0.00 0.00 0.00 0.012048 0.000000 0.00 0.00 0.012048 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.012048 0.00 0.024096 0.00 0.00 0.00 0.00 0.000000 0.00 0.012048 0.012048 0.00 0.00 0.00 0.012048 0.00 0.00 0.00 0.060241 0.012048 0.00 0.000000 0.012048 0.012048 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.072289 0.036145 0.012048 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.036145 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.012048 0.012048 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.000000 0.012048 0.012048 0.00 0.00 0.000000 0.00 0.00 0.024096 0.108434 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.012048 0.00 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.024096 0.00 0.00 0.000000 0.00 0.024096 0.000000 0.00 0.024096 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.012048 0.012048 0.00 0.00 0.012048 0.00 0.00 0.000000 0.00 0.00 0.00 0.012048 0.00 0.000000 0.00 0.012048 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.012048 0.000000 0.000000 0.012048 0.000000 0.012048 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.012048 0.024096 0.000000 0.012048 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00
11 2 OH 0.020000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.010000 0.000000 0.00 0.00 0.00 0.01 0.020000 0.00 0.00 0.00 0.00 0.000000 0.00 0.01000 0.02 0.010000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.020000 0.00 0.01 0.00 0.00 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.030000 0.010000 0.00 0.010000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.000000 0.00 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.010000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.010000 0.00 0.01 0.000000 0.00 0.01 0.000000 0.000000 0.000000 0.040000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.010000 0.030000 0.000000 0.00 0.00 0.000000 0.03 0.00 0.010000 0.000000 0.00 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.020000 0.00 0.010000 0.00 0.00 0.00 0.010000 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.010000 0.00 0.01 0.000000 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.11 0.04 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.01 0.00 0.01 0.000000 0.000000 0.00 0.00 0.000000 0.01 0.00 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.020000 0.01 0.03 0.000000 0.000000 0.02 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.010000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.07 0.05 0.000000 0.00 0.01 0.000000 0.06
12 3 TX 0.010000 0.03 0.000000 0.00 0.00 0.01 0.000000 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.000000 0.090000 0.020000 0.01 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.020000 0.010000 0.01 0.00 0.00 0.00 0.000000 0.00 0.00 0.00 0.00 0.000000 0.00 0.03000 0.02 0.000000 0.00 0.00 0.00 0.00 0.010000 0.010000 0.00 0.00 0.000000 0.010000 0.00 0.00 0.000000 0.000000 0.000000 0.000000 0.00 0.060000 0.00 0.00 0.00 0.00 0.010000 0.00 0.000000 0.000000 0.01 0.00 0.00 0.000000 0.00 0.00 0.01 0.010000 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.010000 0.01 0.00 0.000000 0.00 0.00 0.030000 0.00 0.01 0.00 0.00 0.00 0.000000 0.01 0.00 0.00 0.070000 0.000000 0.00 0.00 0.00 0.00 0.000000 0.000000 0.00 0.02 0.000000 0.00 0.00 0.000000 0.010000 0.000000 0.050000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.000000 0.060000 0.000000 0.00 0.00 0.010000 0.00 0.00 0.010000 0.000000 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.050000 0.01 0.000000 0.01 0.00 0.00 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.020000 0.070000 0.00 0.010000 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.000000 0.00 0.000000 0.00 0.00 0.01 0.000000 0.00 0.00 0.00 0.000000 0.000000 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.000000 0.00 0.000000 0.00 0.01 0.00 0.000000 0.000000 0.00 0.01 0.000000 0.00 0.00 0.010000 0.000000 0.000000 0.010000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.00 0.010000 0.01 0.000000 0.00 0.00 0.000000 0.000000 0.00 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.00 0.000000 0.00 0.00 0.00 0.000000 0.00 0.00 0.000000 0.00

Find the 10 most common venue categories for each of the tennis stadiums & labelling each of the 13 stadiums into different clusters:

Event_Venue Cluster_Labels 1st most common category 2nd most common category 3rd most common category 4th most common category 5th most common category 6th most common category 7th most common category 8th most common category 9th most common category 10th most common category
0 Rod_Laver_Czech 0 Lounge Clothing Store Sporting Goods Shop Shoe Store Skating Rink Lingerie Store Women's Store Cosmetics Shop Jewelry Store Public Bathroom
1 Rod_Laver_Swizz 0 Convention Center Hotel Event Space Exhibit Restaurant Parking Café Bank Fair Mediterranean Restaurant
2 Wimbledon 0 Platform Coffee Shop Bank Fast Food Restaurant Bus Stop Salon / Barbershop Office Shoe Store Grocery Store Stationery Store
3 AZ 0 Building Convenience Store Church Mexican Restaurant Bar Salon / Barbershop Automotive Shop American Restaurant Baseball Field Bakery
4 CA 0 Building Clothing Store Pharmacy Sporting Goods Shop Café Department Store Big Box Store Coworking Space Doctor's Office Bank
5 Aus Open 1 Event Space Tennis Stadium Warehouse General Entertainment Tennis Court Café Concert Hall Food Service Australian Restaurant Bridge
6 US Open 1 Tennis Stadium General Entertainment Tennis Court Clothing Store Lounge Bar Sporting Goods Shop Sandwich Place Food Court Hot Dog Joint
7 French Open 2 Tennis Court Stadium Arts & Entertainment College Classroom French Restaurant Event Space Sporting Goods Shop Office Garden Bus Stop
8 FL 2 Beach Tennis Court Residential Building (Apartment / Condo) Café Gas Station Office Other Great Outdoors Boat or Ferry Harbor / Marina Cuban Restaurant
9 OH 2 Tennis Court Theme Park Water Park Theme Park Ride / Attraction Office Tennis Stadium General Entertainment Parking Photography Lab Golf Course
10 Rod_Laver_Chicago 3 Bar Stadium General Entertainment Outdoor Sculpture Basketball Stadium Sports Bar Parking Hockey Arena Bus Line Sporting Goods Shop
11 MA 3 Bar Platform Hockey Arena General Entertainment Hockey Field Lounge Pizza Place Sporting Goods Shop Moving Target Event Space
12 TX 3 Bar Sports Bar Lounge Event Space Parking Office Residential Building (Apartment / Condo) Italian Restaurant Clothing Store Art Gallery
In [226]:
master_set = master_tennis_most_common.sort_values(by = ['Cluster_Labels']).reset_index(drop=True)
master_set = master_set.drop(master_set.index[[0,1,2,5,7,10]]).reset_index(drop=True)

#Bubble Sort: 
temp = master_set.iloc[0].copy()
master_set.iloc[0] = master_set.iloc[2]
master_set.iloc[2] = temp
master_set
Out[226]:
Event_Venue Cluster_Labels 1st most common category 2nd most common category 3rd most common category 4th most common category 5th most common category 6th most common category 7th most common category 8th most common category 9th most common category 10th most common category
0 US Open 1 Tennis Stadium General Entertainment Tennis Court Clothing Store Lounge Bar Sporting Goods Shop Sandwich Place Food Court Hot Dog Joint
1 CA 0 Building Clothing Store Pharmacy Sporting Goods Shop Café Department Store Big Box Store Coworking Space Doctor's Office Bank
2 AZ 0 Building Convenience Store Church Mexican Restaurant Bar Salon / Barbershop Automotive Shop American Restaurant Baseball Field Bakery
3 FL 2 Beach Tennis Court Residential Building (Apartment / Condo) Café Gas Station Office Other Great Outdoors Boat or Ferry Harbor / Marina Cuban Restaurant
4 OH 2 Tennis Court Theme Park Water Park Theme Park Ride / Attraction Office Tennis Stadium General Entertainment Parking Photography Lab Golf Course
5 MA 3 Bar Platform Hockey Arena General Entertainment Hockey Field Lounge Pizza Place Sporting Goods Shop Moving Target Event Space
6 TX 3 Bar Sports Bar Lounge Event Space Parking Office Residential Building (Apartment / Condo) Italian Restaurant Clothing Store Art Gallery

Utilizing 'Folium Map' to visualize the location of Miami stadium, in Florida, on a map:

Results:

After running the KMeans clustering algorithm on a list of 13 city venues, the city stadiums in the states of 'AZ - Arizona', 'MA - Massachusetts', 'CA- California', 'OH - Ohio' and 'FL-Florida' are found to differ, in neighborhood similarity from the Great stadiums of 'US Open', 'Wimbledon' and 'Chicago Laver Cup' tournament. After exploring each of the 5 shortlisted city destinations in the states of (AZ, MA, CA, FL, OH), it is found that Miami, FL currently does not yet have the sports infrastructure to host an event such as the Laver Cup, in the short-listed location. Since, the Laver Cup is scheduled to be hosted around last of September, 9 months may be too short of a time period for the Federation to fully equip the 'Crandon Tennis Center' with the facilities and environment conducive of creating an ultimate and world-class Tennis experience for the fans. As such, Miami, Florida has been taken off as a candidate city for 2020, however, it may be a hot candidate to choose when the Cup is back to the US, in 2022.

Palm Springs, CA; Boston, MA; Cincinatti, OH; Dallas, TX and Phoenix, AZ are the remaining venues from which Laver Cup Committee much choose to host the next Laver Cup.

NOTE: Since Palm Springs, CA and Cincinatti already host major ATP tournaments, the committee has decided to choose a "fresh venue" for this year's Laver Cup. This leaves the committee to choose between Boston, MA; Dallas, TX and Phoenix, AZ as the final 3 candidate cities to choose from.

To finally choose which one of the 3 cities is closer to U.S. Open in terms of neighborhood similarity of cultivating and inculcating a true Tennis fan experience, another clustering algorithm will be utilized to determine which of the 3 cities matches closer to the neighborhood of the famous 'Flushing Meadows' sports arena.

Displaying Top 10 most common venues between US Open Stadium, Dallas Stadium, Boston Stadium and Phoenix Stadium:

Event_Venue 1st most common category 2nd most common category 3rd most common category 4th most common category 5th most common category 6th most common category 7th most common category 8th most common category 9th most common category 10th most common category
3 AZ Building Convenience Store Church Mexican Restaurant Bar Salon / Barbershop Automotive Shop American Restaurant Baseball Field Bakery
6 US Open Tennis Stadium General Entertainment Tennis Court Clothing Store Lounge Bar Sporting Goods Shop Sandwich Place Food Court Hot Dog Joint
11 MA Bar Platform Hockey Arena General Entertainment Hockey Field Lounge Pizza Place Sporting Goods Shop Moving Target Event Space
12 TX Bar Sports Bar Lounge Event Space Parking Office Residential Building (Apartment / Condo) Italian Restaurant Clothing Store Art Gallery
(11, 4)
(282, 4)

Comparing the top 25 most common venue categories around "US Open" with the category of venues found around stadiums of 'Phoenix', 'Boston' and 'Dallas'.

General Entertainment Clothing Store Tennis Court Lounge Sporting Goods Shop Sandwich Place Bar Restaurant Hot Dog Joint Cocktail Bar Seafood Restaurant Ice Cream Shop Wine Bar Event Space Food Court Deli / Bodega Food & Drink Shop Salad Place Cuban Restaurant Sculpture Garden Fountain Creperie Coffee Shop Fast Food Restaurant
US Open 23.540000 10.70 10.7 8.560000 6.420000 6.420000 6.420000 4.28 4.280000 4.28 4.28 4.280000 4.280000 4.280000 4.280000 2.14 2.14 2.14 2.14 2.14 2.14 2.14 2.140000 2.14
Boston 10.963855 0.00 0.0 6.578313 4.385542 0.000000 21.927711 0.00 2.192771 0.00 0.00 0.000000 2.192771 4.385542 2.192771 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 0.00
Phoenix 0.000000 0.00 0.0 0.000000 0.000000 1.838384 5.515152 0.00 0.000000 0.00 0.00 1.838384 0.000000 0.000000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.838384 0.00
Dallas 1.820000 5.46 0.0 12.740000 3.640000 0.000000 16.380000 1.82 0.000000 3.64 0.00 0.000000 0.000000 10.920000 0.000000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000000 1.82

Visualizing the top 24 most common venue types found around Arthur Ashe Stadium.

Note: The most common venue type, 'Tennis Stadium' has been intentionally removed, as the stadaium(s) are not counted for neighborhood analysis purposes.

Visualizing the top 24 most common venue types found around Arthur Ashe Stadium as a 'HeatMap'

Filtering the DF to only include 'U.S. Open', 'AZ', 'TX' and 'MA':

Cluster_Labels Event_Venue American Restaurant Art Gallery Arts & Crafts Store Arts & Entertainment Asian Restaurant Athletics & Sports Auditorium Australian Restaurant Automotive Shop BBQ Joint Baby Store Bagel Shop Bakery Bank Bar Basketball Court Basketball Stadium Beach Beer Bar Beer Garden Bike Rental / Bike Share Bistro Boat or Ferry Bookstore Botanical Garden Boutique Brewery Bridal Shop Bridge Buffet Building Burger Joint Bus Line Bus Station Bus Stop Business Center Café Camera Store Candy Store Casino Chinese Restaurant Church Circus Clothing Store Cocktail Bar Coffee Shop College Baseball Diamond College Classroom College Stadium Comedy Club Concert Hall Conference Room Convention Center Corporate Cafeteria Cosmetics Shop Coworking Space Creperie Cuban Restaurant Deli / Bodega Diner Doctor's Office Donut Shop Eastern European Restaurant Event Space Exhibit Factory Fair Farm Fast Food Restaurant Food & Drink Shop Food Court Food Service Food Truck Fountain French Restaurant Fried Chicken Joint Furniture / Home Store Garden Gas Station General Entertainment Gift Shop Gourmet Shop Government Building Grocery Store Gym Gym / Fitness Center Hardware Store Health & Beauty Service High School Historic Site History Museum Hockey Arena Hockey Field Hot Dog Joint Hotel Hotel Bar Hotel Pool Ice Cream Shop Indian Restaurant Indoor Play Area Italian Restaurant Jewelry Store Juice Bar Karaoke Bar Kitchen Supply Store Korean Restaurant Laundry Service Light Rail Station Lingerie Store Liquor Store Lounge Massage Studio Mediterranean Restaurant Meeting Room Men's Store Metro Station Mexican Restaurant Middle School Mini Golf Miscellaneous Shop Mobile Phone Shop Monument / Landmark Movie Theater Museum Music Venue Nightclub Office Optical Shop Other Great Outdoors Other Repair Shop Outdoor Event Space Outdoor Sculpture Outdoors & Recreation Paper / Office Supplies Store Park Parking Performing Arts Venue Perfume Shop Pet Store Pharmacy Photography Lab Physical Therapist Pizza Place Platform Plaza Police Station Pool Pool Hall Post Office Pub Public Art Public Bathroom Real Estate Office Recreation Center Recycling Facility Rental Car Location Residential Building (Apartment / Condo) Restaurant Rock Club Roof Deck Rugby Stadium Salad Place Salon / Barbershop Sandwich Place Scenic Lookout Sculpture Garden Seafood Restaurant Shoe Repair Shoe Store Shopping Plaza Skating Rink Smoke Shop Snack Place Soccer Stadium Souvenir Shop Spa Sporting Event Sporting Goods Shop Sports Bar Sports Club Stadium Stationery Store Steakhouse Strip Club Supermarket Sushi Restaurant Swiss Restaurant TV Station Taco Place Tailor Shop Tattoo Parlor Taxi Stand Tea Room Tech Startup Temple Tennis Court Tennis Stadium Toy / Game Store Train Station Tram Station Transportation Service Travel Lounge University Vacation Rental Vegetarian / Vegan Restaurant Video Store Warehouse Warehouse Store Whisky Bar Wine Bar Wine Shop Women's Store Yoga Studio ATM Accessories Store Advertising Agency Arcade Baseball Field Big Box Store Bike Shop Business Service Capitol Building Comfort Food Restaurant Construction & Landscaping Convenience Store Dentist's Office Department Store Dessert Shop Discount Store Dive Bar Dog Run EV Charging Station Electronics Store Fabric Shop Field Fire Station Fish & Chips Shop Food Gastropub General Travel German Restaurant Golf Course Harbor / Marina Hospital Housing Development Kids Store Latin American Restaurant Market Moving Target Nail Salon Newsstand Nightlife Spot Non-Profit Other Nightlife Peruvian Restaurant Pet Service Planetarium Playground Preschool Professional & Other Places Radio Station River School Shopping Mall Skate Park Soccer Field Speakeasy Storage Facility Student Center Supplement Shop Surf Spot Thai Restaurant Theater Theme Park Theme Park Ride / Attraction Thrift / Vintage Store Toll Booth Tourist Information Center Trail Water Park
0 1 US Open 0.010000 0.00 0.0 0.0 0.0 0.00 0.000000 0.0 0.000000 0.010000 0.0 0.0 0.000000 0.000000 0.030000 0.000000 0.00 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.010000 0.010000 0.00 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01 0.000000 0.0 0.05 0.02 0.010000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.00 0.01 0.01 0.01 0.000000 0.0 0.000000 0.0 0.020000 0.0 0.0 0.0 0.0 0.01 0.01 0.020000 0.000000 0.00 0.01 0.0 0.010000 0.0 0.0 0.00 0.110000 0.000000 0.0 0.000000 0.000000 0.000000 0.0 0.000000 0.0 0.000000 0.0 0.0 0.000000 0.000000 0.020000 0.00 0.00 0.0 0.020000 0.01 0.0 0.010000 0.0 0.00 0.0 0.0 0.01 0.000000 0.00 0.0 0.0 0.040000 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.00 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.01 0.0 0.010000 0.0 0.0 0.0 0.0 0.0 0.010000 0.000000 0.000000 0.0 0.0 0.00 0.0 0.0 0.010000 0.000000 0.01 0.0 0.0 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.0 0.0 0.000000 0.02 0.000000 0.00 0.0 0.01 0.000000 0.030000 0.0 0.01 0.02 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.030000 0.000000 0.0 0.010000 0.0 0.01 0.0 0.0 0.0 0.0 0.00 0.000000 0.0 0.000000 0.0 0.0 0.00 0.000000 0.05 0.22 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.020000 0.0 0.0 0.0 0.000000 0.0 0.00 0.0 0.000000 0.0 0.0 0.00 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.00 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.000000 0.00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0
1 0 AZ 0.020202 0.00 0.0 0.0 0.0 0.00 0.010101 0.0 0.030303 0.000000 0.0 0.0 0.020202 0.010101 0.030303 0.010101 0.00 0.0 0.0 0.010101 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.070707 0.010101 0.00 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.00 0.040404 0.0 0.00 0.00 0.010101 0.0 0.0 0.0 0.0 0.000000 0.010101 0.0 0.0 0.020202 0.00 0.00 0.00 0.00 0.010101 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.0 0.00 0.00 0.000000 0.000000 0.00 0.00 0.0 0.000000 0.0 0.0 0.00 0.000000 0.000000 0.0 0.010101 0.010101 0.020202 0.0 0.010101 0.0 0.010101 0.0 0.0 0.000000 0.000000 0.000000 0.00 0.00 0.0 0.010101 0.00 0.0 0.020202 0.0 0.00 0.0 0.0 0.00 0.010101 0.00 0.0 0.0 0.000000 0.010101 0.0 0.0 0.0 0.0 0.030303 0.010101 0.0 0.00 0.0 0.0 0.0 0.000000 0.000000 0.010101 0.00 0.0 0.010101 0.0 0.0 0.0 0.0 0.0 0.010101 0.000000 0.000000 0.0 0.0 0.00 0.0 0.0 0.010101 0.000000 0.00 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.000000 0.00 0.010101 0.00 0.0 0.00 0.030303 0.010101 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.000000 0.010101 0.0 0.000000 0.0 0.00 0.0 0.0 0.0 0.0 0.00 0.010101 0.0 0.010101 0.0 0.0 0.00 0.010101 0.00 0.00 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.010101 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.00 0.0 0.020202 0.0 0.0 0.00 0.010101 0.0 0.0 0.040404 0.020202 0.0 0.000000 0.010101 0.020202 0.010101 0.0 0.0 0.010101 0.010101 0.0 0.0 0.010101 0.00 0.010101 0.0 0.0 0.010101 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.00 0.010101 0.010101 0.010101 0.010101 0.010101 0.000000 0.0 0.010101 0.00 0.010101 0.010101 0.0 0.010101 0.010101 0.010101 0.010101 0.000000 0.0 0.0 0.010101 0.0 0.0 0.0 0.010101 0.0 0.0 0.010101 0.0
2 3 MA 0.000000 0.00 0.0 0.0 0.0 0.00 0.012048 0.0 0.000000 0.012048 0.0 0.0 0.000000 0.000000 0.120482 0.000000 0.00 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.012048 0.000000 0.000000 0.00 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.00 0.000000 0.0 0.00 0.00 0.000000 0.0 0.0 0.0 0.0 0.012048 0.000000 0.0 0.0 0.012048 0.00 0.00 0.00 0.00 0.000000 0.0 0.012048 0.0 0.024096 0.0 0.0 0.0 0.0 0.00 0.00 0.012048 0.012048 0.00 0.00 0.0 0.012048 0.0 0.0 0.00 0.060241 0.012048 0.0 0.000000 0.012048 0.012048 0.0 0.000000 0.0 0.000000 0.0 0.0 0.072289 0.036145 0.012048 0.00 0.00 0.0 0.000000 0.00 0.0 0.000000 0.0 0.00 0.0 0.0 0.00 0.000000 0.00 0.0 0.0 0.036145 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.00 0.0 0.0 0.0 0.012048 0.012048 0.000000 0.00 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.000000 0.012048 0.012048 0.0 0.0 0.00 0.0 0.0 0.024096 0.108434 0.00 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.012048 0.00 0.000000 0.00 0.0 0.00 0.000000 0.000000 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 0.024096 0.0 0.0 0.0 0.0 0.024096 0.000000 0.0 0.024096 0.0 0.00 0.0 0.0 0.0 0.0 0.00 0.000000 0.0 0.000000 0.0 0.0 0.00 0.000000 0.00 0.00 0.0 0.012048 0.012048 0.0 0.0 0.012048 0.0 0.0 0.000000 0.0 0.0 0.0 0.012048 0.0 0.0 0.0 0.012048 0.0 0.00 0.0 0.000000 0.0 0.0 0.00 0.000000 0.0 0.0 0.012048 0.000000 0.0 0.012048 0.000000 0.012048 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.00 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.012048 0.024096 0.0 0.012048 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.0 0.000000 0.00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.012048 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0
3 3 TX 0.010000 0.03 0.0 0.0 0.0 0.01 0.000000 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.000000 0.090000 0.020000 0.01 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.020000 0.010000 0.01 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.00 0.000000 0.0 0.03 0.02 0.000000 0.0 0.0 0.0 0.0 0.010000 0.010000 0.0 0.0 0.000000 0.01 0.00 0.00 0.00 0.000000 0.0 0.000000 0.0 0.060000 0.0 0.0 0.0 0.0 0.01 0.00 0.000000 0.000000 0.01 0.00 0.0 0.000000 0.0 0.0 0.01 0.010000 0.000000 0.0 0.000000 0.000000 0.000000 0.0 0.000000 0.0 0.000000 0.0 0.0 0.010000 0.000000 0.000000 0.01 0.01 0.0 0.000000 0.00 0.0 0.030000 0.0 0.01 0.0 0.0 0.00 0.000000 0.01 0.0 0.0 0.070000 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.02 0.0 0.0 0.0 0.000000 0.010000 0.000000 0.05 0.0 0.010000 0.0 0.0 0.0 0.0 0.0 0.000000 0.060000 0.000000 0.0 0.0 0.01 0.0 0.0 0.010000 0.000000 0.02 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.050000 0.01 0.000000 0.01 0.0 0.00 0.000000 0.000000 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.020000 0.070000 0.0 0.010000 0.0 0.00 0.0 0.0 0.0 0.0 0.01 0.000000 0.0 0.000000 0.0 0.0 0.01 0.000000 0.00 0.00 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.01 0.0 0.000000 0.0 0.0 0.01 0.000000 0.0 0.0 0.010000 0.000000 0.0 0.010000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.0 0.010000 0.01 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.000000 0.01 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0

Apply KMeans clustering to the "master_tennis_set_filtered" to find which of the 3 states / 3 candidate cities is closest to U.S. Open in terms of neighborhood similarity:

NOTE: Cluster size is chosen to be 2, since only 4 neighborhoods/destinations are being compared here and we're interested in finding cities which fall under the same cluster/category as U.S Open.

Event_Venue Cluster_Labels American Restaurant Art Gallery Arts & Crafts Store Arts & Entertainment Asian Restaurant Athletics & Sports Auditorium Australian Restaurant Automotive Shop BBQ Joint Baby Store Bagel Shop Bakery Bank Bar Basketball Court Basketball Stadium Beach Beer Bar Beer Garden Bike Rental / Bike Share Bistro Boat or Ferry Bookstore Botanical Garden Boutique Brewery Bridal Shop Bridge Buffet Building Burger Joint Bus Line Bus Station Bus Stop Business Center Café Camera Store Candy Store Casino Chinese Restaurant Church Circus Clothing Store Cocktail Bar Coffee Shop College Baseball Diamond College Classroom College Stadium Comedy Club Concert Hall Conference Room Convention Center Corporate Cafeteria Cosmetics Shop Coworking Space Creperie Cuban Restaurant Deli / Bodega Diner Doctor's Office Donut Shop Eastern European Restaurant Event Space Exhibit Factory Fair Farm Fast Food Restaurant Food & Drink Shop Food Court Food Service Food Truck Fountain French Restaurant Fried Chicken Joint Furniture / Home Store Garden Gas Station General Entertainment Gift Shop Gourmet Shop Government Building Grocery Store Gym Gym / Fitness Center Hardware Store Health & Beauty Service High School Historic Site History Museum Hockey Arena Hockey Field Hot Dog Joint Hotel Hotel Bar Hotel Pool Ice Cream Shop Indian Restaurant Indoor Play Area Italian Restaurant Jewelry Store Juice Bar Karaoke Bar Kitchen Supply Store Korean Restaurant Laundry Service Light Rail Station Lingerie Store Liquor Store Lounge Massage Studio Mediterranean Restaurant Meeting Room Men's Store Metro Station Mexican Restaurant Middle School Mini Golf Miscellaneous Shop Mobile Phone Shop Monument / Landmark Movie Theater Museum Music Venue Nightclub Office Optical Shop Other Great Outdoors Other Repair Shop Outdoor Event Space Outdoor Sculpture Outdoors & Recreation Paper / Office Supplies Store Park Parking Performing Arts Venue Perfume Shop Pet Store Pharmacy Photography Lab Physical Therapist Pizza Place Platform Plaza Police Station Pool Pool Hall Post Office Pub Public Art Public Bathroom Real Estate Office Recreation Center Recycling Facility Rental Car Location Residential Building (Apartment / Condo) Restaurant Rock Club Roof Deck Rugby Stadium Salad Place Salon / Barbershop Sandwich Place Scenic Lookout Sculpture Garden Seafood Restaurant Shoe Repair Shoe Store Shopping Plaza Skating Rink Smoke Shop Snack Place Soccer Stadium Souvenir Shop Spa Sporting Event Sporting Goods Shop Sports Bar Sports Club Stadium Stationery Store Steakhouse Strip Club Supermarket Sushi Restaurant Swiss Restaurant TV Station Taco Place Tailor Shop Tattoo Parlor Taxi Stand Tea Room Tech Startup Temple Tennis Court Tennis Stadium Toy / Game Store Train Station Tram Station Transportation Service Travel Lounge University Vacation Rental Vegetarian / Vegan Restaurant Video Store Warehouse Warehouse Store Whisky Bar Wine Bar Wine Shop Women's Store Yoga Studio ATM Accessories Store Advertising Agency Arcade Baseball Field Big Box Store Bike Shop Business Service Capitol Building Comfort Food Restaurant Construction & Landscaping Convenience Store Dentist's Office Department Store Dessert Shop Discount Store Dive Bar Dog Run EV Charging Station Electronics Store Fabric Shop Field Fire Station Fish & Chips Shop Food Gastropub General Travel German Restaurant Golf Course Harbor / Marina Hospital Housing Development Kids Store Latin American Restaurant Market Moving Target Nail Salon Newsstand Nightlife Spot Non-Profit Other Nightlife Peruvian Restaurant Pet Service Planetarium Playground Preschool Professional & Other Places Radio Station River School Shopping Mall Skate Park Soccer Field Speakeasy Storage Facility Student Center Supplement Shop Surf Spot Thai Restaurant Theater Theme Park Theme Park Ride / Attraction Thrift / Vintage Store Toll Booth Tourist Information Center Trail Water Park
0 US Open 0 0.010000 0.00 0.0 0.0 0.0 0.00 0.000000 0.0 0.000000 0.010000 0.0 0.0 0.000000 0.000000 0.030000 0.000000 0.00 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.010000 0.010000 0.00 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.01 0.000000 0.0 0.05 0.02 0.010000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.00 0.01 0.01 0.01 0.000000 0.0 0.000000 0.0 0.020000 0.0 0.0 0.0 0.0 0.01 0.01 0.020000 0.000000 0.00 0.01 0.0 0.010000 0.0 0.0 0.00 0.110000 0.000000 0.0 0.000000 0.000000 0.000000 0.0 0.000000 0.0 0.000000 0.0 0.0 0.000000 0.000000 0.020000 0.00 0.00 0.0 0.020000 0.01 0.0 0.010000 0.0 0.00 0.0 0.0 0.01 0.000000 0.00 0.0 0.0 0.040000 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.00 0.0 0.0 0.0 0.000000 0.000000 0.000000 0.01 0.0 0.010000 0.0 0.0 0.0 0.0 0.0 0.010000 0.000000 0.000000 0.0 0.0 0.00 0.0 0.0 0.010000 0.000000 0.01 0.0 0.0 0.0 0.0 0.0 0.01 0.0 0.0 0.0 0.0 0.0 0.000000 0.02 0.000000 0.00 0.0 0.01 0.000000 0.030000 0.0 0.01 0.02 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.030000 0.000000 0.0 0.010000 0.0 0.01 0.0 0.0 0.0 0.0 0.00 0.000000 0.0 0.000000 0.0 0.0 0.00 0.000000 0.05 0.22 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.020000 0.0 0.0 0.0 0.000000 0.0 0.00 0.0 0.000000 0.0 0.0 0.00 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.00 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.000000 0.00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0
1 AZ 0 0.020202 0.00 0.0 0.0 0.0 0.00 0.010101 0.0 0.030303 0.000000 0.0 0.0 0.020202 0.010101 0.030303 0.010101 0.00 0.0 0.0 0.010101 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.070707 0.010101 0.00 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.00 0.040404 0.0 0.00 0.00 0.010101 0.0 0.0 0.0 0.0 0.000000 0.010101 0.0 0.0 0.020202 0.00 0.00 0.00 0.00 0.010101 0.0 0.000000 0.0 0.000000 0.0 0.0 0.0 0.0 0.00 0.00 0.000000 0.000000 0.00 0.00 0.0 0.000000 0.0 0.0 0.00 0.000000 0.000000 0.0 0.010101 0.010101 0.020202 0.0 0.010101 0.0 0.010101 0.0 0.0 0.000000 0.000000 0.000000 0.00 0.00 0.0 0.010101 0.00 0.0 0.020202 0.0 0.00 0.0 0.0 0.00 0.010101 0.00 0.0 0.0 0.000000 0.010101 0.0 0.0 0.0 0.0 0.030303 0.010101 0.0 0.00 0.0 0.0 0.0 0.000000 0.000000 0.010101 0.00 0.0 0.010101 0.0 0.0 0.0 0.0 0.0 0.010101 0.000000 0.000000 0.0 0.0 0.00 0.0 0.0 0.010101 0.000000 0.00 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.000000 0.00 0.010101 0.00 0.0 0.00 0.030303 0.010101 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.000000 0.010101 0.0 0.000000 0.0 0.00 0.0 0.0 0.0 0.0 0.00 0.010101 0.0 0.010101 0.0 0.0 0.00 0.010101 0.00 0.00 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.010101 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.00 0.0 0.020202 0.0 0.0 0.00 0.010101 0.0 0.0 0.040404 0.020202 0.0 0.000000 0.010101 0.020202 0.010101 0.0 0.0 0.010101 0.010101 0.0 0.0 0.010101 0.00 0.010101 0.0 0.0 0.010101 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.00 0.010101 0.010101 0.010101 0.010101 0.010101 0.000000 0.0 0.010101 0.00 0.010101 0.010101 0.0 0.010101 0.010101 0.010101 0.010101 0.000000 0.0 0.0 0.010101 0.0 0.0 0.0 0.010101 0.0 0.0 0.010101 0.0
2 MA 1 0.000000 0.00 0.0 0.0 0.0 0.00 0.012048 0.0 0.000000 0.012048 0.0 0.0 0.000000 0.000000 0.120482 0.000000 0.00 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.012048 0.000000 0.000000 0.00 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.00 0.000000 0.0 0.00 0.00 0.000000 0.0 0.0 0.0 0.0 0.012048 0.000000 0.0 0.0 0.012048 0.00 0.00 0.00 0.00 0.000000 0.0 0.012048 0.0 0.024096 0.0 0.0 0.0 0.0 0.00 0.00 0.012048 0.012048 0.00 0.00 0.0 0.012048 0.0 0.0 0.00 0.060241 0.012048 0.0 0.000000 0.012048 0.012048 0.0 0.000000 0.0 0.000000 0.0 0.0 0.072289 0.036145 0.012048 0.00 0.00 0.0 0.000000 0.00 0.0 0.000000 0.0 0.00 0.0 0.0 0.00 0.000000 0.00 0.0 0.0 0.036145 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.00 0.0 0.0 0.0 0.012048 0.012048 0.000000 0.00 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.000000 0.012048 0.012048 0.0 0.0 0.00 0.0 0.0 0.024096 0.108434 0.00 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.012048 0.00 0.000000 0.00 0.0 0.00 0.000000 0.000000 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 0.024096 0.0 0.0 0.0 0.0 0.024096 0.000000 0.0 0.024096 0.0 0.00 0.0 0.0 0.0 0.0 0.00 0.000000 0.0 0.000000 0.0 0.0 0.00 0.000000 0.00 0.00 0.0 0.012048 0.012048 0.0 0.0 0.012048 0.0 0.0 0.000000 0.0 0.0 0.0 0.012048 0.0 0.0 0.0 0.012048 0.0 0.00 0.0 0.000000 0.0 0.0 0.00 0.000000 0.0 0.0 0.012048 0.000000 0.0 0.012048 0.000000 0.012048 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.00 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.012048 0.024096 0.0 0.012048 0.00 0.000000 0.000000 0.000000 0.000000 0.000000 0.012048 0.0 0.000000 0.00 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.012048 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0
3 TX 1 0.010000 0.03 0.0 0.0 0.0 0.01 0.000000 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.000000 0.090000 0.020000 0.01 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.000000 0.020000 0.010000 0.01 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.00 0.000000 0.0 0.03 0.02 0.000000 0.0 0.0 0.0 0.0 0.010000 0.010000 0.0 0.0 0.000000 0.01 0.00 0.00 0.00 0.000000 0.0 0.000000 0.0 0.060000 0.0 0.0 0.0 0.0 0.01 0.00 0.000000 0.000000 0.01 0.00 0.0 0.000000 0.0 0.0 0.01 0.010000 0.000000 0.0 0.000000 0.000000 0.000000 0.0 0.000000 0.0 0.000000 0.0 0.0 0.010000 0.000000 0.000000 0.01 0.01 0.0 0.000000 0.00 0.0 0.030000 0.0 0.01 0.0 0.0 0.00 0.000000 0.01 0.0 0.0 0.070000 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.02 0.0 0.0 0.0 0.000000 0.010000 0.000000 0.05 0.0 0.010000 0.0 0.0 0.0 0.0 0.0 0.000000 0.060000 0.000000 0.0 0.0 0.01 0.0 0.0 0.010000 0.000000 0.02 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 0.0 0.0 0.050000 0.01 0.000000 0.01 0.0 0.00 0.000000 0.000000 0.0 0.00 0.00 0.0 0.0 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.020000 0.070000 0.0 0.010000 0.0 0.00 0.0 0.0 0.0 0.0 0.01 0.000000 0.0 0.000000 0.0 0.0 0.01 0.000000 0.00 0.00 0.0 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.01 0.0 0.000000 0.0 0.0 0.01 0.000000 0.0 0.0 0.010000 0.000000 0.0 0.010000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.000000 0.0 0.0 0.010000 0.01 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.0 0.000000 0.000000 0.0 0.000000 0.01 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.000000 0.01 0.000000 0.000000 0.0 0.000000 0.000000 0.000000 0.000000 0.000000 0.0 0.0 0.000000 0.0 0.0 0.0 0.000000 0.0 0.0 0.000000 0.0

Applying 'PCA' to reduce the dimensionality of the 4 candidate cities into 3 features or dimensions. The cluster centers for the 4 candidate cities can be visualized in the below 3-D projected graph. As can be seen below, 'Phoenix' is identified to be the closest to 'US Open', as compared to 'Boston' and 'Dallas' in the 3-D cluster space.

Note: The 2 clusters can be identified in colors of blue and red, respectively.

Visualizing the neighborhood and type of venues around the chosen "Arizona Veterans Memorial Stadium" in Phoenix, AZ.

Map Center: 'Arizona Veterans Memorial Stadium'

Conclusion:

The Multi-sport stadium in Phoenix, AZ is one of the best locations for the respective Tennis Federation / Organization to host the next Laver Cup, to be hosted in 2020*. Since the neighborhood, in terms of the types of venues around the stadium, is most similar to that of the U.S. Open stadium in Flushing Meadows (both 'US Open' and 'AZ' state fall under the same cluster), there's expected to be a good turn-around of tennis fans to watch and support the intensive and celebratory 3-Days Laver Cup event, initiated by Roger Federer and Rod Laver.

On visualizing the neighborhood of Phoenix, AZ, we find a very similar city and lanscape to that of U.S. Open venue, around the 'USTA Billie Jean National Stadium'.

Moreover, both venues ('Arizona Veterans Memorial Stadium' in Phoenix and 'U.S. Open Stadiums' in NYC) have a high number of 'Sandwich places', 'Coffee Shops', 'American Restaurants' and 'Bars'. These venue types are very condusive of a celebratory environment and also attract inter-state and international trourists alike, especially if there's a large sporting event at the heart of it all.

*Update: The Laver Cup committee has chosen Boston, MA as the destination for Laver Cup-2020, which is a great option per the metrics analyzed as part of this Capstone Project. However, the Laver Cup committee may look into the option of hosting the next Laver Cup (hosted outside Europe), to be in Phoenix, AZ for 2022, scheduled from September 25th to 27th. Phoenix, AZ has the famous "Arizona Veterans Memorial Stadium" which is multi-purpose sports auditorium. The committee must look to strategise an expansion plan in and around the stadium to create an ultimate fan experience and bring world of Tennis to the hometown of Arizona. This will be a great opportunity to spread Tennis in southern parts of the US, such as Arizona and Texas, where Tennis is not yet the top 3 sports celebrated, in terms of viewer-ship and sponsorship.